The research goal is to solve the problems of low accuracy and long time existing in traditional teaching reform performance evaluation methods, a performance evaluation method of teaching reform based on hierarchical multi-task deep learning is proposed. Under the principle of constructing the evaluation index system, the evaluation indicator system should be constructed. The weight of the evaluation index is calculated through the analytic hierarchy process, and the calculation result of the evaluation weight is taken as the model input sample. A hierarchical multi-task deep learning model for teaching reform performance evaluation is built, and the final teaching reform performance score is obtained. Through relevant experiments, it is proved that compared with the experimental comparison method, this method has the advantages of high evaluation accuracy and short time, and can be further applied in relevant fields.

The European Union Rights Management Directive 2014/26/EU, provides regulatory oversight of European Union (EU) Collective Management Organizations (CMOs). However, the Directive has no provision indicating how members of EU CMOs may conduct non-financial audits of their CMO income and reporting. This paper addresses the problem of a lack of an audit method through a case study of the five writer members of the music group Duran Duran, who have been members of the UK's CMO for performing rights - the Performing Rights Society (PRS) for over 35 years. The paper argues a new audit CMO member method that can address the lacunae regarding the absence of CMO member right to audit a CMO and an applicable CMO audit method.

Multi-criteria inventory classification (MCIC) is popularly used to aid managers in categorising the inventory. Researchers have used numerous mathematical models and approaches, but few resorted to unsupervised machine-learning techniques to address MCIC. This study uses the expectation-maximisation (EM) algorithm to estimate the parameters of the Gaussian mixture model (GMM), a popular unsupervised machine learning algorithm, for ABC inventory classification. The EM-GMM algorithm is sensitive to initialisation, which in turn affects the results. To address this issue, two different initialisation procedures have been proposed for the EM-GMM algorithm. Inventory classification outcomes from 14 existing MCIC models have been given as inputs to study the significance of the two proposed initialisation procedures of the EM-GMM algorithm. The effectiveness of these initialisation procedures corresponding to various inputs has been analysed toward inventory management performance measures, i.e., fill rate, total relevant cost, and inventory turnover ratio.

Simulations have been shown to be an effective tool in traditional learning environments; however, as distance learning grows in popularity, the need to examine simulation effectiveness in this environment has become paramount. A casual-comparative design was chosen for this study to determine whether students using a computer-based instructional simulation in hybrid and fully online environments learned better than traditional classroom learners. The study spans a period of 6 years beginning fall 2008 through spring 2014. The population studied was 281 undergraduate business students self-enrolled in a 200-level microcomputer application course. The overall results support previous studies in that computer simulations are most effective when used as a supplement to face-to-face lectures and in hybrid environments.

This longitudinal, quasi-experimental study investigated students’ cognitive personality type using the Myers-Briggs personality Type Indicator (MBTI) in Internet-based Online and Face-to-Face (F2F) modalities. A total of 1154 students enrolled in 28 Online and 32 F2F sections taught concurrently over a period of fourteen years. The study measured whether the sample is similar to the national average percentage frequency of all 16 different personality types; whether specific personality type students preferred a specific modality of instructions and if this preference changed over time; whether learning occurred in both class modalities; and whether specific personality type students learned more from a specific modality. Data was analyzed using regression, t-test, frequency, and Chi-Squared. The study concluded that data used in the study was similar to the national statistics; that no major differences in preference occurred over time; and that learning did occur in all modalities, with more statistically significant learning found in the Online modality versus F2F for Sensing, Thinking, and Perceiving types. Finally, Sensing and Thinking (ST) and Sensing and Perceiving (SP) group types learned significantly more in Online modality versus F2F.

The authors present the results of a study conducted at a comprehensive, urban, coeducational, land-grant university. A quasi-experimental design was chosen for this study to compare student performance in two different classroom environments, traditional versus flipped. The study spanned 3 years, beginning fall 2012 through spring 2015. The participants included 433 declared business majors who self-enrolled in several sections of the Management Information Systems course during the study. The results of the current study mirrored those of previous works as the instructional method impacted students’ final grade. Thus, reporting that the flipped classroom approach offers flexibility with no loss of performance when compared to traditional lecture-based environments.

Aim/Purpose: The purpose of this study was to examine whether grit was a contributing factor to student persistence and success at minority serving institutions. Background: A number of studies conducted in the past fifteen years have concluded that grit is a positive predictor of achievement across many domains. But, is grit really the ultimate panacea for student success? This longitudinal study sought to answer that question by specifically focusing on business students attending a mid-Atlantic minority-serving institution that primarily serves low-income and first generation learners. Methodology: The research study under consideration used quantitative methods for data collection and analysis. It was initiated in the Fall of 2014 with the administration of the standard 12-item Grit assessment to all freshmen students enrolled in a university business department. Students were then followed longitudinally over a five year period with GPA and persistence to graduation documented. During the analyses, grit score was compared to participant first year GPA’s as well as retention and persistence to graduation via comparison tables and ANOVAs. Contribution: A lack of substantive studies conducted at HBCUs and other minority serving institutions poses a major gap in the existing literature available on grit. A number of authors have put forth a call to action for faculty at minority serving institutions to conduct meaningful studies focused on grit and student persistence in order to better inform the HBCU community. This study is specifically purposed to help fill some of the gaps in the available literature. The results of the research presented in this paper hopefully shed light on the need to explore non-cognitive factors that may affect student performance. In particular, research should explore factors that may, or may not, contribute to the success of under prepared college students in particular those who are from low income, first generation, and minority groups. This form of exploration is part of a commitment to positive student outcomes. Findings: According to the findings, there is a significant positive correlation between higher grit scores and both GPA and persistence to graduation. First year GPA, however, was not found to be a reliable predictor of academic success. Recommendations for Practitioners: As part of a commitment to positive student outcomes, faculty and administrators in higher education must be constantly exploring factors that may, or may not, impact student success. Recommendation for Researchers: The results of this research help to shed light on the need to explore elements that may help to contribute to the success of under prepared college students in particular those who are from low income, first generation, and minority groups Future Research: The authors conclude that while building the grittiness of freshmen students may lead to positive student outcomes, grit alone might not be enough. In fact, they postulate that grittiness without clarity of purpose, positive self-efficacy, and growth mindset may mean that students who may be gritty may not be exerting their energies appropriately. During the next phase, a model that is currently under development will be used as part of a mindset intervention to edify students about grit, growth mindset, locus of control/self-efficacy, and clarity of purpose. A complimentary research study examining student performance and perceptions will also be conducted.

This work investigated the suitability of a new tool for decision support in training programs of high performance athletes. The aim of this study was to find a reliable and robust measure of the fitness of an athlete for use as a tool for adjusting training schedules. We examined the use of heart rate recovery percentage (HRr%) for this purpose, using a two-phased approach. Phase 1 consisted of testing the suitability of HRr% as a measure of aerobic fitness, using a modified running test specifically designed for high-performance team running sports such as football. Phase 2 was conducted over a 12-week training program with two different training loads. HRr% measured aerobic fitness and a running time-trial measured performance. Consecutive measures of HRr% during phase 1 indicated a Pearson’s r of 0.92, suggesting a robust measure of aerobic fitness. During phase 2, HRr% reflected the training load and significantly increased when the training load was reduced between weeks 4 to 5. This work shows that HRr% is a robust indicator of aerobic fitness and provides an on-the-spot index that is useful for training load adjustment of elite-performance athletes.

Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly) is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications) was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties.

For more than two decades, knowledge management (KM) has been examined in the literature and considered a basic factor in business management. The purpose of this article is to explore the ability of knowledge management to achieve small and medium-sized enterprise (SME) innovation and business performance. Data analysis procedures of PLS-SEM was used to analyze the data based on responses from the owners of 903 companies in industry, construction, services, and trade in the Region of Murcia (Spain) through a self-directed survey. The results show that KM has a significant influence on innovation but the influence on the level of performance of SMEs is insignificant. However, training employees as part of KM showed no significant influence on innovation in SMEs. It is important for leaders and managers to have greater openness to changes in the implementation and proper execution of KM. This work contributes primarily to the development of the literature on knowledge management and its relationship with innovation and business performance.

Aim/Purpose: The present study investigates the relationship between the five-factor model (FFM) of personality traits and sales performance in Pakistan. Background: Personality is a well-researched area in which numerous studies have examined the correlation between personality traits and job performance. In this study, a positive effect between the various dimensions of the five-factor model (extraversion, agreeableness, conscientiousness, emotional stability, and open to experience) and sales performance in Pakistan is investigated. Methodology: Pearson’s correlation values as well as analysis methodologies were employed to gather descriptive statistics, reliability analysis, correlation analysis, and use the analytical hierarchy process (AHP). Cronbach’s alpha value helped determine the internal consistency of the group items. Questionnaires were distributed among 600 salespersons in various cities of Pakistan from April 2015 to January 2016. Subsequently, 510 questionnaires were acquired for the sample. Contribution: The current study contributes to the literature on personality traits and sales performance by applying empirical evidence from sales managers in three industries of Pakistan: pharmaceutical, insurance, and electronics. Findings: The results affirmed a positive effect of the five-factor model on sales performance among various industries in Pakistan. The effect of each sub-factor from the five-factor model was examined autonomously. There is a favorable benefit to sales managers in considering FFM when making hiring decisions. Impact on Society: FFM offers important insights into personality traits that work well within Pakistani sales industry structure. Future Research: A broader rendering of the effects of FFM on sales organizations in other geographical locations around Pakistan should be considered. Additionally, an extended study should be conducted to investigate the effects of FFM on female sales employees involving religious and cultural forces within that country.

Aim/Purpose: This study aims to investigate the relationship between the knowledge management (KM) process and the performance of construction companies. The ultimate goal is to promote better efficiency and competitive advantage in the construction industry by making the best use of knowledge. Background: While attention to KM is currently on the rise, as shown by the number of studies conducted, research on KM in the construction industry of Indonesia is still very rare. However, organizational learning as the implementation of KM provides an opportunity to improve the construction industry, and thus there is an urgency to conduct research on this topic. Methodology: This study lasted for three months and used the survey method, with 100 questionnaires distributed to contractors of grade 6 and 7 on the islands of Java and Borneo in Indonesia. A total of 54 returned questionnaires were deemed complete and eligible for further analysis. Data analysis was performed using the structural equation modeling method with partial least squares (SEM PLS). Contribution: This study helps to measure the relationship value of the KM process and company performance. Findings: The results of this study indicate that the process of KM has a significant and positive influence on company performance, and there is a positive interaction in the process of KM and company performance as well. Recommendations for Practitioners: Construction companies need to perceive that activities undertaken in a construction project should always be assumed to be a KM process in order to make strategic and effective decisions that can result in improvements to customers, finance, internal business, learning, and growth. Recommendation for Researchers: Research on the KM process and information technology needs to be developed more, so that construction companies can apply this knowledge to explore problems and create solutions, resulting in methods to facilitate efficiency and effectiveness. Impact on Society: This paper helps to understand that KM activities provide initial benefits and guidance for companies that want to apply KM. Future Research: Innovative and new ideas to cultivate the KM process in the construction industry need to be explored and developed to improve the implementation.

Aim/Purpose: This explanatory study aimed to determine the mediating role of ERP in the relation between the effect of a socio-technical approach and decision-making environment, and firms’ sustainable performance. Background: Although earlier studies have discussed the critical success factors of the failure or success of an ERP system and the extent to which it achieves its desired objectives, the current study focused on the significant impact of socio-technical elements and decision-making environment on the success of the ERP system (i.e., sustainable performance). In addition, the lack of research on ERP as a mediator in the above relationship motivated this study to bridge the literature gap. Methodology: The data was collected using questionnaires distributed to 233 randomly selected employees of three multinational companies (BP, LUKOIL, and Eni) operating in Iraq. The structural equation modeling was employed to test the hypothesized relationships. Contribution: The study contributes to the literature by examining the mediating role of the ERP system in the relationship between socio-technical elements and the decision-making environment, as well as, the moderating role of organizational culture in the relationship between socio-technical elements and ERP systems. Findings: The results showed that ERP is a significant mediator between the linkage of socio-technical elements and the decision-making environment while organizational culture has an insignificant moderating role in the relationship between socio-technical elements and ERP systems. Recommendations for Practitioners: In a developing country like Iraq, there is a need to implement ERP to achieve better sustainable performance through change management and organizational development that ultimately work towards enhancing individual capabilities, knowledge, and training. Recommendation for Researchers: The researchers are recommended to conduct an in-depth study of the phenomenon based on theoretical and empirical grounds, particularly in light of the relationship of socio-technical elements and decision-making environments. Impact on Society: This study provides a reference for organizations with similar cultural backgrounds in using ERP systems to minimize pollution in Iraqi context. Future Research: A more in-depth study can be performed using a bigger sample, which not only includes the oil industry but also the other industries.

Aim/Purpose: This paper identifies the antecedents that affect E-Banking (EB) adoption and investigates the relationship between the level of EB adoption and the performance of private banks. Background: Rapid technological advancement has transformed the business environment dramatically. These advancements particularly the Internet has reshaped the way businesses operate. Over the last decade, the banking industry has become highly complex and competitive and operates in a highly volatile and unpredictable global economy. With the increasing demand for electronic services, banks are harnessing EB technology to improve their products and services. Methodology: Quantitative research using Structural Equation Modelling (SEM) was carried out with a sample size of 211 by sending questionnaires to employees of six banks in Khartoum, Sudan. The study is based on different technology theories and models. Contribution: The study provides insights into the employees’ perception of EB adoption in their banking transactions. Findings: The results showed that four factors are significant in the adoption of EB in Sudan. However, training and user trust were insignificant in determining its adoption. Moreover, the level of adoption of EB significantly affected private bank performance. Recommendations for Practitioners: Private banks in Sudan that are interested in EB might find these findings helpful in guiding their technology adoption and application initiatives. Recommendation for Researchers: To validate the research model, cross data from different countries are encouraged to apply the model to capture the differences and similarities among them. In addition, a longitudinal research could be conducted to gather data for adoption process over a longer period rather than one point of time, to investigate antecedents and bank performance outcomes by the end of the study period. Other antecedents and outcomes could possibly be included to improve the power of the study model. Impact on Society: This study provides a reference for banks with similar developing country backgrounds in adopting EB to enhance their performance. Moreover, knowledge of antecedents and outcomes of EB adoption could be positively reflected in service quality performance. Future Research: This research is limited to the employees’ perspective, and future research could consider the perception of customers from a developing country towards EB adoption.

Aim/Purpose: The objective of this study was to assess the interrelationships among knowledge management infrastructure, knowledge management process, intellectual capital, and organization performance. Background: Although knowledge management capability is extensively used by organizations, reaching their maximum financial and non-financial performances has not been fully researched. Therefore, organizations need to optimize their performance by exploiting knowledge management capability through the accumulation of intellectual capital, where the new competitiveness is shifting from tangible to intangible resources. Methodology: This study adopted a positivist philosophy and deductive approach to accomplish the main goal of this research. Moreover, this research employed a quantitative approach since this study is concerned with causal relationship between variables. A questionnaire-based survey was designed to evaluate the research model using a convenience sample of 134 employees from the food industry sector in Jordan. Surveyed data was examined following the structural equation modeling procedures. Contribution: This study highlighted the potential benefits of applying the knowledge management capabilities, intellectual capital, and organizational performance to the food industrial sector in Jordan. Future research suggestions are also provided. Findings: Results indicated that knowledge management infrastructure had a positive effect on knowledge management process. In addition, knowledge management process impacted positively intellectual capital and organization performance and mediated the relationship between knowledge management infrastructure and intellectual capital. However, knowledge management infrastructure did not positively associate to organization performance. Recommendations for Practitioners: The current model is designed to help managers and decision makers to improve their management capabilities as well as their organization financial and non-financial performance through exploiting the organizational knowledge management infrastructure and intellectual capital approaches. Recommendation for Researchers: Our findings can be used as a base of knowledge to conduct further studies about knowledge management capabilities, intellectual capital, and organization performance following different criteria and research procedures. Impact on Society: The designed model highlights a significant organizational performance approach that can influence Jordanian food industrial sector positively. Future Research: The current designed research model can be applied and assessed further in other sectors including banking and industrial sectors across developed and developing countries. Also, we suggest that in addition to focusing on knowledge management process and intellectual capital as mediating variables, future research could test our findings in a longitudinal study and examine how to affect financial and non-financial performance.

Aim/Purpose: This study analyzes the mechanism of Internet capability (IC) driving knowledge creation performance (KCP). We consider the mediating role of strategic flexibility and the moderating role of informatization density. Background: The key to achieving KCP for firms is to transform knowledge created into new products or services and to realize the economic benefits. However, the research has not paid enough attention to firms’ KCP. Based on dynamic capability theory, this study empirically reveals how firms drive KCP through Internet capability. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet capability, strategic flexibility, and KCP and uses hierarchical regression to test the moderating role of informatization density. Contribution: First, this study expands research on knowledge creation and focuses on the further achievement of knowledge creation performance. The study also enriches the exploration of KCP in the Internet context and deepens the research on the internal mechanism by which Internet capability influences KCP. Second, this study highlights the important role of informatization density in the Internet context and expands the research on the impact of external factors on the internal mechanism. Findings: First, Internet capability has a significantly positive effect on both strategic flexibility and KCP. Furthermore, Internet capability directly impacts strategic flexibility, yet it affects KCP both directly and indirectly through strategic flexibility, which confirms that strategic flexibility is a partial mediator in the relationship between Internet capability and KCP. Second, strategic flexibility positively influences KCP. Third, informatization density has a significant moderating effect on the relationship between Internet capability and KCP. Recommendations for Practitioners: The results indicate that firms should consider the importance of Internet capability and strategic flexibility for KCP in the Internet context. This study also provides a theoretical basis that could guide the Chinese government’s informatization construction of the industrial chain. Recommendation for Researchers: Researchers could further explore the role of other mediator variables (e.g., business process management, organizational agility) and consider the role of other moderator variables (e.g., resource commitment, learning orientation). Impact on Society: This study provides a reference for enterprises with similar cultural backgrounds in using Internet capability to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct longitudinal studies to increase the robustness of the conclusions.

Aim/Purpose: Two research objectives were addressed in this study. The first objective was to determine the effect of knowledge management orientation behaviour on business performance, and the second objective was to investigate the mediating effect of market orientation in the relationship between knowledge management orientation behaviour and business performance. Background: In business strategic perspective, the idea of knowledge management has been discussed widely. However, there is a lack of study exploring the notion of knowledge management orientation especially in the perspective of Indonesia’s creative economy sector. Methodology: One hundred and thirty one participants were involved in this study. They were economy creative practitioners in Indonesia. Data were analysed by using Partial Least Squares. Contribution: Upon the completion of the research objectives, this study contributes to both theoretical and practical perspectives. From a theoretical standpoint, this study proposes a conceptual model explaining the relationship among knowledge management orientation behaviour, market orientation, and business performance in Indonesia’s creative economy sector. As this study found a significant effect of knowledge sharing in market orientation and market orientation in business performance, the study showed the mediation role of market orientation in the relationship between knowledge sharing and business performance. From a practical perspective, this study implies a guideline for business practitioners in enhancing business through the application of knowledge management orientation behaviour. Findings: The results show that organizing memory, knowledge absorption, and knowledge receptivity has a direct significant effect on business performance. However, in affecting business performance, knowledge sharing must be mediated by market orientation. Recommendations for Practitioners: Based on the results of the study, practitioners should enhance their behaviour in implementing knowledge management in terms of increasing business performance. In addition, it is suggested that business practitioners must be market driven, as market orientation was found to have an important role in affecting business performance. Recommendation for Researchers: Future researchers might integrate other constructs such as innovation, marketing capabilities, or organizational learning with this current conceptual model to have more comprehensive insight about the relationship between knowledge management orientation and business performance. Impact on Society: This study suggests that business practitioners must have knowledge management driven behaviour as well as market orientation to enhance the performance of their business. Future Research: Future research might add other variables to make the conceptual model more comprehensive and also replicate this study into different industrial settings.

Aim/Purpose: Despite the fact that the plethora of studies demonstrate the positive impact of information technology (IT) capabilities on SMEs performance, the understanding of underlying mechanisms through which IT capabilities affect the firm performance is not yet clear. This study fills these gaps by explaining the roles of absorptive capacity and corporate entrepreneurship. The study also elaborates the effect of IT capability dimensions (IT integration and IT alignment) upon the SMEs performance outcomes through the mediating sequential process of absorptive capacity and corporate entrepreneurship. Methodology: This study empirically tests a theoretical model based on the Dynamic Capability View (DCV), by using the partial least square (PLS) technique with a sample of 489 manufacturing SMEs in Pakistan. A survey is employed for the data collection by following the cluster sampling approach. Contribution: This research contributes to the literature of IT by bifurcating the IT capability into two dimensions, IT integration and IT alignment, which allows us to distinguish between different sources of IT capabilities. Additionally, our findings shed the light on the dynamic capability view by theoretically and empirically demonstrating how absorptive capacity and corporate entrepreneurship sequentially affect the firms' performance outcomes. At last, this study contributes to the literature of SMEs by measuring the two levels of performance: innovation performance and firm performance. Findings: The results of the analysis show that the absorptive capacity and the corporate entrepreneurship significantly mediate the relationship between both dimensions of IT capability and performance outcomes.

Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), etc. Knowledge about metrics properties needs to be systematized to simplify the design and use of the metrics. Methodology: A qualitative study was conducted to achieve the objectives of identifying related peer-reviewed research studies, literature reviews, critical thinking and inductive reasoning. Contribution: The main contribution of this paper is in ordering knowledge of performance metrics and enhancing understanding of their structure and properties by proposing a new typology, generic primary metrics mathematical formula and a visualization chart Findings: Based on the analysis of the structure of numerous performance metrics, we proposed a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics. The paper identified three (3) key components (dimensions) that determine the structure and properties of primary metrics: method of determining point distance, method of normalization, method of aggregation of point distances over a data set. For each component, implementation options have been identified. The suggested new typology has been shown to cover a total of over 40 commonly used primary metrics Recommendations for Practitioners: Presented findings can be used to facilitate teaching performance metrics to university students and expedite metrics selection and implementation processes for practitioners Recommendation for Researchers: By using the proposed typology, researchers can streamline development of new metrics with predetermined properties Impact on Society: The outcomes of this study could be used for improving evaluation results in machine learning regression, forecasting and prognostics with direct or indirect positive impacts on innovation and productivity in a societal sense Future Research: Future research is needed to examine the properties of the extended metrics, composite metrics, and hybrid sets of metrics. Empirical study of the metrics is needed using R Studio or Azure Machine Learning Studio, to find associations between the properties of primary metrics and their “numerical” behavior in a wide spectrum of data characteristics and business or research requirements

Aim/Purpose: This study aimed to examine the effect of marketing knowledge management (MKM) on bank performance via the mediating role of the Fintech innovation in Jordanian commercial banks. Background: An extensive number of studies found a significant relationship between Marketing knowledge management and bank performance (e.g., Akroush & Al-Mohammad, 2010; Hou & Chien 2010; Rezaee & Jafari, 2015; Veismoradi et al., 2013). However, there remains a lack of clarity regarding the relationship between marketing knowledge management (MKM) and bank performance (BP). Furthermore, the linkage between MKM and BP is not straightforward but, instead, includes a more complicated relationship. Therefore, it is argued that managing marketing knowledge management assets and capabilities can enhance performance via the role of financial innovation as a mediating factor on commercial banks; to date, however, there is no empirical evidence. Methodology: Based on a literature review, knowledge-based theory, and financial innovation theory, an integrated conceptual framework has been developed to guide the study. A quantitative approach was used, and the data was collected from 336 managers and employees in all 13 Jordanian commercial banks using online and in hand instruments. Structural equation modeling (SEM) was used to analyze and verify the study variables. Contribution: This article contributes to theory by filling a gap in the literature regarding the role of marketing knowledge management assets and capabilities in commercial banks operating in a developing country like Jordan. It empirically examined and validated the role of Fintech innovation as mediators between marketing knowledge management and bank performance Findings: The main findings revealed that marketing knowledge management had a significant favorable influence on bank performance. Fintech innovation acted as partial mediators in this relationship. Recommendations for Practitioners: Commercial banks should be fully aware of the importance of knowledge management practices to enhance their financial innovation and bank performance. They should also consider promoting a culture of practicing knowledge management processes among their managers and employees by motivating and training to promote innovations. Recommendation for Researchers: The result endorsed Fintech innovation’s mediating effect on the relationship between the independent variable, marketing knowledge management (assets and capabilities), and the dependent variable bank performance, which was not addressed before; thus, it needs further validation. Future Research: The current designed research model can be applied and assessed further in other sectors, including banking and industrial sectors across developed and developing countries. It would also be of interest to introduce other variables in the study model that can act as consequences of MKM capabilities, such as financial and non-financial performance measures

Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes.

Aim/Purpose: The purpose of this study is to investigate the mechanism of the front/back-office structure affecting new service development (NSD) performance and examine the role of knowledge transfer in the relationship between front/back-office structure and NSD. Background: The separation of front and back-office has become the prevailing trend of the organizational transformation of modern service enterprises in the digital era. Yet, the influence of front and back-office separation dealing with new service development has not been widely researched. Methodology: Building on the internal social capital perspective, a multivariate regression analysis was conducted to investigate the impact of front/back-office structure on the NSD performance through knowledge transfer as an intermediate variable. The data was collected through a survey questionnaire from 198 project-level officers in the commercial banking industry of China. Contribution: This study advances the understanding of front/back-office structure’s influence mechanism on new service development activity. It reveals that knowledge transfer plays a critical role in bridging the impact of front and back-office separation to NSD performance under the trend of digitalization of service organizations. Findings: This study verified the positive effects of front/back-office social capital on NSD performance. Moreover, knowledge transfer predicted the variation in NSD performance and fully mediated the effect of front/back-office social capital on NSD performance. Recommendations for Practitioners: Service organizations should optimize knowledge transfer by promoting the social capital between front and back-office to overcome the negative effect organizational separation brings to NSD. Service and other organizations could explore developing an internal social network management platform, by which the internal social network could be visualized and dynamically managed. Recommendation for Researchers: The introduction of information and communications technology not only divides the organization into front and back-office, but also reduces the face-to-face customer contact. The impacts of new forms of customer contact to new service development and knowledge transfer between customer and service organizations call for further research. Along with the digital servitization, some manufacturing organizations also separate front and back-offices. The current model can be applied and assessed further in manufacturing and other service sectors. Impact on Society: The conclusion of this study guides us to pay attention to the construction of social capital inside organizations with front/back-office structure and implicates introducing and developing sociotechnical theory in front/back-office issue undergoing technological revolution. Future Research: As this study is based on the retail banking industry, similar studies are called upon in other service sectors to identify differences and draw more general conclusions. In addition, as the front and back-offices are being replaced increasingly by information technology such as artificial intelligence (AI), it is necessary to advance the research on front/back-office research with a new theoretical perspective, such as sociotechnical theory.

Aim/Purpose: This study aimed to investigate the impact of innovation management and learning orientation as the mechanisms playing the role of an intermediate relationship between entrepreneurial leadership and organisational performance of small and medium enterprises (SMEs) in Kuwait. Background: SMEs are currently among the principal economic instruments in most industrialised and developing countries. The contribution of SMEs can be viewed from various perspectives primarily related to the crucial role they play in developing entrepreneurial activities, employment generation, and improving innovativeness. Developing countries, including Kuwait and other countries, in the Gulf Cooperation Council (GCC), have recognised the key role played by SMEs as a strong pillar of growth. Consequently, many governments have formulated policies and programmes to facilitate the growth and success of SMEs. Unfortunately, the organisational performance of SMEs in developing countries, particularly in Kuwait, remains below expectations. The lagged growth could be due to a lack of good managerial practices and increasing competition that negatively impact their performance. Numerous researchers discovered the positive effect of entrepreneurial leadership on SMEs’ performance. However, a lack of clarity remains regarding the direct impact of entrepreneurial leadership on SMEs’ performance, especially in developing countries. Therefore, the nexus between entrepreneurial leadership and organisational performance is still indecisive and requires further studies. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather data within a specific period. The data were collected by distributing a survey questionnaire to Kuwaiti SMEs’ owners and Chief Executive Officers (CEOs) via online and on-hand instruments. A total of 384 useable questionnaires were obtained. Moreover, the partial least square-structural equation modelling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: The current study contributed to the existing literature by developing a moderated mediation model integrating entrepreneurial leadership, innovation management, and learning orientation. The study also investigated their effect on the organisational performance of SMEs. The study findings also bridged the existing significant literature gap regarding the role of these variables on SMEs’ performance in developing countries, particularly in Kuwait, due to the dearth of studies linking these variables in this context. Furthermore, this study empirically confirmed the significant effect of innovation management and learning orientation as intermediate variables in strengthening the relationship between entrepreneurial leadership and organisational performance in the settings of Kuwait SMEs, which has not been verified previously. Findings: The study findings showed the beneficial and significant impact of entrepreneurial leadership and innovation management on SME’s organisational performance. The relationship between entrepreneurial leadership and SMEs’ organisational performance is fundamentally mediated by innovation management and moderated by learning orientation. Recommendations for Practitioners: The present study provides valuable insights and information regarding the factors considered by the government, policymakers, SMEs’ stakeholders, and other authorities in the effort to increase the organisational performance level and facilitate the growth of SMEs in Kuwait. SMEs’ owners or CEOs should improve their awareness and knowledge of the importance of entrepreneurial leadership, innovation management, and learning orientation. These variables will have beneficial effects on the performance and assets to achieve success and sustainability if adopted and managed systematically. This study also recommends that SMEs’ entrepreneurs and top management should facilitate supportive culture by creating and maintaining an organisational climate and structure that encourages learning behaviour and innovation mindset among individuals. The initiative will motivate them towards acquiring, sharing, and utilising knowledge and increasing their ability to manage innovation systemically in all production processes to adapt to new technologies, practices, methods, and different circumstances. Recommendation for Researchers: The study findings highlighted the mediating effect of innovation management on the relationship between entrepreneurial leadership (the independent variable) and SMEs’ organisational performance (the dependent variable) and the moderating effect of learning orientation in the same nexus. These relationships were not extensively addressed in SMEs of developing countries and require further validation. Impact on Society: This study aims to influence the management strategies and practices adopted by entrepreneurs and policymakers who work in SMEs in developing countries. The effect will be reflected in the development of their firms and the national economy in general. Future Research: Future research should investigate the conceptual research framework against the backdrop of other developing economies and in other business settings to generalise the results. Future investigation should seek to establish the effect of entrepreneurial leadership style on other mechanisms, such as knowledge management processes, which could function with entrepreneurial leadership to improve SMEs’ performance efficiently. In addition, future studies may include middle and lower-level managers and employees, leading to more positive outcomes.

Aim/Purpose: The study attempts to analyse the influences of knowledge management capacity on company performance and supply chain practices. It also examines whether supply chain practices significantly and positively impact company performance. Background: Knowledge management capacity is an essential tactical resource that enables the integration and coordination among supply chain stakeholders, but research examining the link between knowledge management capacity and supply chain practices and their impacts on company performance remains scarce. Methodology: The study uses correlation analysis and factor analysis to confirm the theoretical framework’s validity and structural equation modelling to test hypotheses. The data are obtained from 115 halal food firms in China (with a response rate of 82.7%). Contribution: This study’s findings contribute to the Social Capital Theory by presenting the impacts of different supply chain practices on company performance. The findings also suggest the impact of intangible resources on enhancing company performance, contributing to the Resource-based View Theory. These results are a crucial contribution to both academicians and corporate managers working in the Halal food industry. Managers can apply these findings to discover and adopt knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Findings: This study is an initial effort that provides empirical evidence regarding the relationships among supply chain, knowledge management, and company performance from the perspective of China’s halal food industry. The results prove that knowledge management capacity is the supply chains’ primary success determinant and influencer. Besides, knowledge management capacity positively influences company performance, and supply chain practices directly influence company performance. Recommendations for Practitioners: Managers can apply these study findings to determine and increase knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Recommendation for Researchers: The study presents a new theoretical framework and empirical evidence for surveying halal food businesses in China. Impact on Society: These results are a significant contribution to the research field and industry focusing on halal foods. Future Research: First, this research focuses only on halal food businesses in China; thus, it is essential to re-examine the hypothesized relations between the constructs in other Chinese business segments and regions. Next, the effect of variables and practices on the theorized framework should be taken into account and examined in other industries and nations.

Aim/Purpose: This paper aimed to examine the impact of learning orientation on organizational performance of small and medium enterprises (SMEs) via the mediating role of total quality management (TQM) practices and the moderating role of innovation culture. Background: SMEs’ organizational performance in developing countries, particularly in Kuwait, remains below expectation due to increasing competition and inadequate managerial practices that negatively impact their performance. Although several studies had revealed a significant effect of learning orientation on SMEs’ performance, the direct impact of learning orientation on their performance is still unclear. Thus, the link between learning orientation and organizational performance remains inconclusive and requires further examination. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. The data were collected by distributing a survey questionnaire to the owners and Chief Executive Officers (CEOs) of Kuwaiti SMEs using online and on-hand instruments with 384 useable data obtained. Furthermore, the partial least square-structural equation modeling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: This study bridged the significant gap in the role of learning orientation on SMEs’ performance in developing countries, specifically Kuwait. In this sense, a conceptual model was introduced, comprising a learning orientation, TQM practices, innovation culture, and organizational performance. In addition, this study confirmed the significant influence of TQM practices and innovation culture as intermediate variables in strengthening the relationship between learning orientation and organizational performance, which has not yet been verified in Kuwait. Findings: The results in this study revealed that learning orientation had a significant impact on organizational performance of SMEs in Kuwait. It could be observed that TQM practices play an important role in mediating the relationship between learning orientation and performance of SMEs, as well as that innovation culture plays an important moderating role in the same relation. Recommendations for Practitioners: This study provided a framework for the decision-makers of SMEs on the significant impact of the antecedents that enhanced the level of organizational performance. Hence, owners/CEOs of SMEs should improve their awareness and knowledge of the importance of learning orientation, TQM practices, and innovation culture since it could significantly influence their performance to achieve success and sustainability when adopted and managed systematically. The CEOs should also consider building an innovation culture in the internal environment, which enables them to transform new knowledge and ideas into innovative methods and practices. Recommendation for Researchers: The results in this study highlighted the mediating effect of TQM practices on the relationship between learning orientation (the independent variable) and organizational performance (the dependent variable) of SMEs and the moderating effect of innovation culture in the same nexus. These relationships were not extensively addressed in SMEs and thus required further validation. Impact on Society: This study also influenced the management strategies and practices adopted by entrepreneurs and policymakers working in SMEs in developing countries, which is reflected in their development and the national economy. Future Research: Future studies should apply the conceptual framework of this study and assess it further in other sectors, including large firms in developing and developed countries, to generalize the results. Additionally, other mechanisms should be introduced as significant antecedents of SMEs’ performance, such as market orientation, technological orientation, and entrepreneurial orientation, which could function with learning orientation to influence organizational performance effectively.

Aim/Purpose: This research aims to analyze the effect of human resource management on humanitarian operations performance, using humanitarian organizations in Malaysia as a case. Background: Humanitarian organizations need to develop and continue effective on-the-job human resource management, such as training and development and managing employee performance to enhance the performance of their humanitarian operations. Methodology: The sampling technique that was conducted is probability sampling. In particular, the technique is called stratified sampling. This technique is chosen because it is involving the division of a population into a smaller group, called “strata”. The questionnaire survey was distributed to humanitarian organizations in Malaysia to collect research data, and PLS-SEM analysis was conducted to validate the conceptual model. Contribution: This research focuses on the effect of human resource management on humanitarian operations performance in humanitarian organizations with consistent training to ensure successful humanitarian operations. Findings: The results of PLS-SEM analysis confirmed that Training and Employee Development, Recruitment and Employee Selection, and Communicative Management Style are significantly correlated with humanitarian operations performance, giving 75.7% variations which means that these human resource management are critical factors for increasing humanitarian operations performance in Malaysian humanitarian organizations. Recommendations for Practitioners: This research will enhance humanitarian operations performance for humanitarian organizations, in-line policies outlined under the Malaysia National Security Council Directive No. 20, and benefit the field of disaster management. Recommendation for Researchers: This research can be used by the authorized individual involved in humanitarian operations to satisfy the needs of the victims, which ultimately contributes to the performance of these humanitarian organizations. Impact on Society: This research highlighted the human resource management that is vital for humanitarian organizations, which will increase humanitarian operations performance in an organization. Future Research: This study is conducted in the context of humanitarian organizations in Malaysia. It is unclear whether the key findings of this study can be generalized. Therefore, it is suggested that, in future research, the current research model should be extended to include different countries for validation.

Aim/Purpose: Acquisitions play a pivotal role in the growth strategy of a firm. Extensive resources and time are dedicated by a firm toward the identification of prospective acquisition candidates. The Indian manufacturing sector is currently experiencing significant growth, organically and inorganically, through acquisitions. The principal aim of this study is to explore models that can predict acquisitions and compare their performance in the Indian manufacturing sector. Background: Mergers and Acquisitions (M&A) have been integral to a firm’s growth strategy. Over the years, academic research has investigated multiple models for predicting acquisitions. In the context of the Indian manufacturing industry, the research is limited to prediction models. This research paper explores three models, namely Logistic Regression, Decision Tree, and Multilayer Perceptron, to predict acquisitions. Methodology: The methodology includes defining the accounting variables to be used in the model which have been selected based on strong theoretical foundations. The Indian manufacturing industry was selected as the focus, specifically, data for firms listed in the Bombay Stock Exchange (BSE) between 2010 and 2022 from the Prowess database. There were multiple techniques, such as data transformation and data scrubbing, that were used to mitigate bias and enhance the data reliability. The dataset was split into 70% training and 30% test data. The performance of the three models was compared using standard metrics. Contribution: The research contributes to the existing body of knowledge in multiple dimensions. First, a prediction model customized to the Indian manufacturing sector has been developed. Second, there are accounting variables identified specific to the Indian manufacturing sector. Third, the paper contributes to prediction modeling in the Indian manufacturing sector where there is limited research. Findings: The study found significant supporting evidence for four of the proposed hypotheses indicating that accounting variables can be used to predict acquisitions. It has been ascertained that statistically significant variables influence acquisition likelihood: Quick Ratio, Equity Turnover, Pretax Margin, and Total Sales. These variables are intrinsically linked with the theories of liquidity, growth-resource mismatch, profitability, and firm size. Furthermore, comparing performance metrics reveals that the Decision Tree model exhibits the highest accuracy rate of 62.3%, specificity rate of 66.4%, and the lowest false positive ratio of 33.6%. In contrast, the Multilayer Perceptron model exhibits the highest precision rate of 61.4% and recall rate of 64.3%. Recommendations for Practitioners: The study findings can help practitioners build custom prediction models for their firms. The model can be developed as a live reference model, which is continually updated based on a firm’s results. In addition, there is an opportunity for industry practitioners to establish a benchmark score that provides a reference for acquisitions. Recommendation for Researchers: Researchers can expand the scope of research by including additional classification modeling techniques. The data quality can be enhanced by cross-validation with other databases. Textual commentary about the target firms, including management and analyst quotes, provides additional insight that can enhance the predictive power of the models. Impact on Society: The research provides insights into leveraging emerging technologies to predict acquisitions. The theoretical basis and modeling attributes provide a foundation that can be further expanded to suit specific industries and firms. Future Research: There are opportunities to expand the scope of research in various dimensions by comparing acquisition prediction models across industries and cross-border and domestic acquisitions. Additionally, it is plausible to explore further research by incorporating non-financial data, such as management commentary, to augment the acquisition prediction model.

Aim/Purpose: In this paper, we present an RFM model-based telecom customer churn system for better predicting and analyzing customer churn. Background: In the highly competitive telecom industry, customer churn is an important research topic in customer relationship management (CRM) for telecom companies that want to improve customer retention. Many researchers focus on a telecom customer churn analysis system to find out the customer churn factors for improving prediction accuracy. Methodology: The telecom customer churn analysis system consists of three main parts: customer segmentation, churn prediction, and churn factor identification. To segment the original dataset, we use the RFM model and K-means algorithm with an elbow method. We then use RFM-based feature construction for customer churn prediction, and the XGBoost algorithm with SHAP method to obtain a feature importance ranking. We chose an open-source customer churn dataset that contains 7,043 instances and 21 features. Contribution: We present a novel system for churn analysis in telecom companies, which encompasses customer churn prediction, customer segmentation, and churn factor analysis to enhance business strategies and services. In this system, we leverage customer segmentation techniques for feature construction, which enables the new features to improve the model performance significantly. Our experiments demonstrate that the proposed system outperforms current advanced customer churn prediction methods in the same dataset, with a higher prediction accuracy. The results further demonstrate that this churn analysis system can help telecom companies mine customer value from the features in a dataset, identify the primary factors contributing to customer churn, and propose suitable solution strategies. Findings: Simulation results show that the K-means algorithm gets better results when the original dataset is divided into four groups, so the K value is selected as 4. The XGBoost algorithm achieves 79.3% and 81.05% accuracy on the original dataset and new data with RFM, respectively. Additionally, each cluster has a unique feature importance ranking, allowing for specialized strategies to be provided to each cluster. Overall, our system can help telecom companies implement effective CRM and marketing strategies to reduce customer churn. Recommendations for Practitioners: More accurate churn prediction reduces misjudgment of customer churn. The acquisition of customer churn factors makes the company more convenient to analyze the reasons for churn and formulate relevant conservation strategies. Recommendation for Researchers: The research achieves 81.05% accuracy for customer churn prediction with the Xgboost and RFM algorithms. We believe that more enhancements algorithms can be attempted for data preprocessing for better prediction. Impact on Society: This study proposes a more accurate and competitive customer churn system to help telecom companies conserve the local markets and reduce capital outflows. Future Research: The research is also applicable to other fields, such as education, banking, and so forth. We will make more new attempts based on this system.

Aim/Purpose: This study utilized a comprehensive framework to investigate the adoption of Business Analytics (BA) and its effects on performance in commercial banks in Jordan. The framework integrated the Technological-Organizational-Environmental (TOE) model, the Diffusion of Innovation (DOI) theory, and the Resource-Based View (RBV). Background: The recent trend of utilizing data for business operations and decision-making has positively impacted organizations. Business analytics (BA) is a leading technique that generates valuable insights from data. It has gained considerable attention from scholars and practitioners across various industries. However, guidance is lacking for organizations to implement BA effectively specific to their business contexts. This research aims to evaluate factors influencing BA adoption by Jordanian commercial banks and examine how its implementation impacts bank performance. The goal is to provide needed empirical evidence surrounding BA adoption and outcomes in the Jordanian banking sector. Methodology: The study gathered empirical data by conducting an online questionnaire survey with senior and middle managers from 13 commercial banks in Jordan. The participants were purposefully selected, and the questionnaire was designed based on relevant and well-established literature. A total of 307 valid questionnaires were collected and considered for data analysis. Contribution: This study makes a dual contribution to the BA domain. Firstly, it introduces a research model that comprehensively examines the factors that influence the adoption of BA. The proposed model integrates the TOE framework, DOI theory, and RBV theory. Combining these frameworks allows for a comprehensive examination of BA adoption in the banking industry. By analyzing the technological, organizational, and environmental factors through the TOE framework, understanding the diffusion process through the DOI theory, and assessing the role of resources and capabilities through the RBV theory, researchers and practitioners can better understand the complex dynamics involved. This integrated approach enables a more nuanced assessment of the factors that shape BA adoption and its subsequent impact on business performance within the banking industry. Secondly, it uncovers the effects of BA adoption on business performance. These noteworthy findings stem from a rigorous analysis of primary data collected from commercial banks in Jordan. By presenting a holistic model and delving into the implications for business performance, this research offers valuable insights to researchers and practitioners alike in the field of BA. Findings: The findings revealed that various technological (data quality, complexity, compatibility, relative advantage), organizational (top management support, organizational readiness), and environmental (external support) factors are crucial in shaping the decision to adopt BA. Furthermore, the study findings demonstrated a positive relationship between BA adoption and performance outcomes in Jordanian commercial banks. Recommendations for Practitioners: The findings suggest that Jordanian commercial banks should enforce data quality practices, provide clear standards, invest in data quality tools and technologies, and conduct regular data audits. Top management support is crucial for fostering a data-driven decision-making culture. Organizational readiness involves having the necessary resources and skilled personnel, as well as promoting continuous learning and improvement. Highlighting the benefits of BA helps overcome resistance to technological innovation and encourages adoption by demonstrating improved decision-making processes and operational efficiency. Furthermore, external support is crucial for banks to adopt Business Analytics (BA). Banks should partner with experienced vendors to gain expertise and incorporate best practices. Vendors also provide training and technical support to overcome technological barriers. Compatibility is essential for optimal performance, requiring managers to modify workflows and IT infrastructure. Complexity, including data, organizational, and technical complexities, is a major obstacle to BA adoption. Banks should take a holistic approach, focusing on people, processes, and technology, and prioritize data quality and governance. Building a skilled team, fostering a data-driven culture, and investing in technology and infrastructure are essential. Recommendation for Researchers: The integration of the TOE framework, the DOI theory, and the RBV theory can prove to be a powerful approach for comprehensively analyzing the various factors that influence BA adoption within the dynamic banking industry. Furthermore, this combined framework enables us to gain deeper insights into the subsequent impact of BA adoption on overall business performance. Impact on Society: Examining the factors influencing BA adoption in the banking industry and its subsequent impact on business performance can have wide-ranging societal implications. It can promote data-driven decision-making, enhance customer experiences, strengthen fraud detection, foster financial inclusion, contribute to economic growth, and trigger discussions on ethical considerations. Future Research: To further advance future research, there are several avenues to consider. One option is to broaden the scope by including a larger sample size, allowing for a more comprehensive analysis. Another possibility is to investigate the impact of BA adoption on various performance indicators beyond the ones already examined. Additionally, incorporating qualitative research methods would provide a more holistic understanding of the organizational dynamics and challenges associated with the adoption of BA in Jordanian commercial banks.

Aim/Purpose: The major challenges for firms to initiate corporate social responsibility (CSR) arise from resource constraints, complexity, and uncertainty. Consuming considerable financial and human resources is the main difficulty for smaller firms or those operating in less profitable industries, and the lack of immediate outputs from CSR initiatives poses a challenge for firms in prioritizing and assessing their effectiveness. Background: To better integrate CSR management into overall business strategy and decision-making processes, Blockchain technology (BCT) could potentially offer a feasible and optimal alternative to CSR reports. Methodology: This study uses the fixed effects regression by way of the Least Squares Dummy Variable (LSDV) approach in STATA to analyze the direct effect of CSR management on business performance and the moderating effect of BCT adoption on this relationship with a panel data set of 5810 observations collected from the 874 listed companies in 2015 in Taiwan Stock Exchange through 2021. Contribution: This study contributes to the literature by shedding light on the organizational factors that influence BCT adoption. Findings: The findings show that firms with high levels of CSR management have better business performance. Additionally, the adoption of BCT strengthens the positive relationship between CSR management and business performance, but it cannot replace the fundamental principles of CSR. Finally, firm size does not significantly affect BCT adoption, indicating that companies of all sizes have an equal opportunity to adopt BCT, which can help to level the playing field in terms of resources available to different firms. Recommendations for Practitioners: This study suggests that firms managing CSR practices have better business performance, and the adoption of BCTs further enhances this positive relationship. However, BCT adoption does not have the same positive effect on business performance as CSR practices. Additionally, this research can help to inform public policy related to BCT adoption and diffusion. Recommendation for Researchers: By exploring the factors that influence BCT adoption, future researchers can provide insights into the key challenges and opportunities faced by organizations of different sizes and help to develop strategies for promoting the effective adoption of BCT. Impact on Society: Given the limitations of current CSR reporting, the understanding gained from BCT applications can provide companies with an alternative mechanism to foster progress in CSR implementation. Future Research: Firstly, while the fixed-effects model might have dampened the power of explanation because it only captures within-unit variation and ignores between-unit variation, the explanatory power is further limited due to only integrating two independent variables in this model. Because of limited data availability, this study only utilizes CSR_Report and firm_size as independent variables. Future studies can consider more key factors and may lead to different results. Additionally, panel data is collected from Taiwan and, therefore, may not be representative of the broader population. Future researchers integrating the Stock Exchange of different countries are recommended.

Aim/Purpose: This study investigates the relationship between dual network embedding, dual entrepreneurial bricolage, and knowledge-creation performance. Background: The importance of new ventures for innovation and economic growth has been fully endorsed. Establishing incubation organizations to help new startups overcome constraints and dilemmas has become the consensus of various countries. In particular, the number of Chinese makerspaces has rapidly increased. Startups in the makerspaces form a loosely coupled dual network to cooperate and share resources, especially knowledge. Methodology: By convenience sampling, 400 startups in the makerspaces in Fujian Province, China were selected for the questionnaire survey study. In total, 307 valid responses were collected, yielding a response rate of 76.8%. The survey data were analyzed for hypothesis testing, using the PL-SEM technique with the AMOS20.0 software. Contribution: At the theoretical level, this research supplements the exploration of the influencing factors of the entrepreneurial bricolage of startups at the network level. It deepens the research on the internal mechanism of the dual network embeddedness affecting the knowledge-creation performance. In practice, it provides a theoretical basis and management inspiration for startups in makerspaces to overcome the inherent disadvantage of being too small and weak to explore innovative paths. Findings: First, relational embedding of startups in makerspaces directly affects knowledge-creation performance. Second, dual entrepreneurial bricolage plays a mediating role in diversity. Selective entrepreneurial bricolage plays a partial mediating role between relationship embedding and knowledge-creation performance. Parallel entrepreneurial bricolage plays a complete intermediary role between structural embedding and knowledge-creation performance. Dual entrepreneurial bricolage plays a complete intermediary role between knowledge embedding and knowledge-creation performance. Recommendations for Practitioners: Enterprises in the makerspaces should make dynamic adjustments to the network embedded state and dual entrepreneurial bricolage to improve knowledge-creation performance. When startups conduct selective entrepreneurship bricolage, they should strengthen relational and knowledge embeddedness to improve their relationship strength and tacit knowledge acquisition. When startups conduct parallel entrepreneurship bricolage, structural and knowledge embedding should be strengthened to improve the position of enterprises in the network to acquire diversified knowledge to explore and discover new business opportunities and project resources. Recommendation for Researchers: The heterogeneity of industries and regions may impact the dual network embedding mechanism of startups. Researchers can choose a wider range of regions and industries for sampling. Impact on Society: This study provides a theoretical basis and management inspiration for startups to overcome the inherent disadvantage of being too small and weak to explore innovative paths. It provides a basis to support startups in unleashing innovation vitality and achieving healthy growth. Future Research: Previous studies have shown that network relationships and bricolage behavior have a certain relationship with the enterprise life cycle. Future research can adopt a longitudinal research design across time points, which will increase the explanatory power of research conclusions.