Aim/Purpose: This paper reports our implementation of a prototype system, namely PRATO (Proposals Reviewers Automated Taxonomy-based Organization), for automatic assignment of proposals to reviewers based on categorized tracks and partial matching of reviewers’ profiles of research interests against proposal keywords. Background: The process of assigning reviewers to proposals tends to be a complicated task as it involves inspecting the matching between a given proposal and a reviewer based on different criteria. The situation becomes worse if one tries to automate this process, especially if a reviewer partially matches the domain of the paper at hand. Hence, a new controlled approach is required to facilitate the matching process. Methodology: Proposals and reviewers are organized into categorized tracks as defined by a tree of hierarchical research domains which correspond to the university’s colleges and departments. In addition, reviewers create their profiles of research interests (keywords) at the time of registration. Initial assignment is based on the matching of categorized sub-tracks of proposal and reviewer. Where the proposal and a reviewer fall under different categories (sub-tracks), assignment is done based on partial matching of proposal content against re-viewers’ research interests. Jaccard similarity coefficient scores are calculated of proposal keywords and reviewers’ profiles of research interest, and the reviewer with highest score is chosen. The system was used to automate the process of proposal-reviewer assignment at the Umm Al-Qura University during the 2017-2018 funding cycle. The list of proposal-reviewer assignments generated by the system was sent to human experts for voting and subsequently to make final assignments accordingly. With expert votes and final decisions as evaluation criteria, data system-expert agreements (in terms of “accept” or “reject”) were collected and analyzed by tallying frequencies and calculating rejection/acceptance ratios to assess the system’s performance. Contribution: This work helped the Deanship of Scientific Research (DSR), a funding agency at Umm Al-Qura University, in managing the process of reviewing proposals submitted for funding. We believe the work can also benefit any organizations or conferences to automate the assignment of papers to the most appropriate reviewers. Findings: Our developed prototype, PRATO, showed a considerable impact on the entire process of reviewing proposals at DSR. It automated the assignment of proposals to reviewers and resulted in 56.7% correct assignments overall. This indicates that PRATO performed considerably well at this early stage of its development. Recommendations for Practitioners: It is important for funding agencies and publishers to automate reviewing process to obtain better reviewing quality in a timely manner. Recommendation for Researchers: This work highlighted a new methodology to tackle the proposal-reviewer assignment task in an automated manner. More evaluation might be needed with consideration of different categories, especially for partially matched candidates. Impact on Society: The new methodology and knowledge about factors influencing the implementation of automated proposal-reviewing systems will help funding agencies and publishers to improve the quality of their internal processes. Future Research: In the future, we plan to examine PRATO’s performance on different classification schemes where specialty areas can be represented in graphs rather than trees. With graph representation, the scope for reviewer selection can be widened to include more general fields of specialty. Moreover, we will try to record the reasons for rejection to identify accurately whether the rejection was due to improper assignment or other reasons.

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: The first goal is to develop a decision support system for pricing and production amounts for a firm facing high levels of product returns. The second goal is to improve the management of the product returns process. Background: This study was conducted at a food importer and manufacturer in Israel facing a very high rate of product returns, much of which is eventually discarded. The firm’s products are commonly considered to be a low-cost generic alternative and are therefore popular among low-income families. Methodology: A decision support module was added to the plant’s business information system. The module is based on a supply chain pricing model and uses the sales data to infer future demand’s distribution. Ergonomic models were used to improve the design of the returns warehouse and the handling of the returns. Contribution: The decision support system allows to improve the plant’s pricing and quantity planning. Consequently, it reduced the size of product returns. The new design of the returns process is expected to improve worker’s productivity, reduces losses and results in safer outcomes. This study also demonstrates a successful integration and of a theoretical economical model into an information system. Findings: The results show the promise of incorporating pricing supply chain models into informing systems to achieve a practical business task. We were able to construct actual demand distributions from the data and offer actual pricing recommendations that reduce the number of returns while increasing potential profits. We were able to identify key deficiencies in the returns operations and added a module to the decisions support system that improves the returns management and links it with the sales and pricing modules. Finally, we produced a better warehouse design that supports efficient and ergonomic product returns handling. Recommendations for Practitioners: This work can be replicated for different suppliers, manufacturers and retailers that suffer from product returns. They will benefit from the reduction in returns, as well as the decrease in the losses associated with these returns. Recommendation for Researchers: It is worthwhile to research whether decision support systems can be applied to other aspects of the organizations’ operations. Impact on Society: Product returns is a lose-lose situation for producers, retailers and customers. Moreover, mismanagement of these returns is harmful for the environment and may result in the case of foods, in health hazards. Reducing returns and improving the handling improves sustainability and is beneficial for society. Future Research: The decision support system’s underlying pricing model assumes a specific business setting. This can be extended using other pricing models and applying them in a similar fashion to the current application.

Aim/Purpose: The primary purpose of this study is to investigate the factors that impact the behavioral intention to use social media (SM) for knowledge sharing (KS) in the disaster relief (DR) context. Background: With the continuing growth of SM for KS in the DR environment, disaster relief organizations across the globe have started to realize its importance in streamlining their processes in the post-implementation phase. However, SM-based KS depends on the willingness of members to share their knowledge with others, which is affected by several technological, social, and organizational factors. Methodology: A survey was conducted in Somalia to gather primary data from DR practitioners, using purposive sampling as the technique. The survey collected 214 valid responses, which were then analyzed with the PLS-SEM approach. Contribution: The study contributes to an understanding of the real-life hurdles faced by disaster relief organizations by expanding on the C-TAM-TPB model with the inclusion of top management support, organizational rewards, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust factors. Additionally, it provides useful recommendations to managers of disaster relief organizations on the key factors to consider. Findings: The findings recorded that perceived usefulness, ease of use, top management support, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust were critical factors in determining behavioral intention (BI) to use SM-based KS in the DR context. Furthermore, the mediator variables were attitude, subjective norms, and perceived behavioral control. Recommendations for Practitioners: Based on the research findings, it was determined that management should create different discussion forums among the disaster relief teams to ensure the long-term use of SM-based KS within DR organizations. They should also become involved in the discussions for disaster-related knowledge such as food supplies, shelter, or medical relief that disaster victims need. Disaster relief managers should consider effective and adequate training to enhance individual knowledge and self-efficacy since a lack of training may increase barriers and difficulties in using SM for KS during a DR process. Recommendation for Researchers: The conceptual model, further empirically investigated, can be employed by other developing countries in fostering acceptance of SM for KS during disaster relief operations. Impact on Society: Disaster relief operations can be facilitated using social media by considering the challenges DR practitioners face during emergencies. Future Research: In generalizing this study’s findings, other national or global disaster relief organizations should consider, when applying and testing, the research instruments and proposed model. The researchers may extend this study by collecting data from managers or administrators since they are different types of users of the SM-based KS system.

Aim/Purpose: This conceptual review analyzes the designs of global health virtual communities of practice (VCoPs) programming reported in the empirical literature and proposes a new typology of their functioning. The purpose of this review is to provide clarity on VCoP learning stages of (co)evolution and insight into VCoP (re)development efforts to best meet member, organization, and network needs against an ever-evolving landscape of complexity in global health. Background: Since the COVID-19 pandemic, the field of global health has seen an uptick in the use of VCoPs to support continuous learning and improve health outcomes. However, evidence of how different combinations of programmatic designs impact opportunities for learning and development is lacking, and how VCoPs evolve as learning networks has yet to be explored. Methodology: Following an extensive search for literature in six databases, thematic analysis was conducted on 13 articles meeting the inclusion criteria. This led to the development and discussion of a new typology of VCoP phases of learning (co)evolution. Contribution: Knowledge gained from this review and the new categorization of VCoPs can support the functioning and evaluation of global health training programs. It can also provide a foundation for future research on how VCoPs influence the culture of learning organizations and networks. Findings: Synthesis of findings resulted in the categorization of global health VCoPs into five stages (slightly evolving, somewhat revolving, moderately revolving, highly revolving, and coevolving) across four design domains (network development, general member engagement before/after sessions, general member engagement during sessions, and session leadership). All global health VCoPs reviewed showed signs of adaptation and recommended future evolution. Recommendations for Practitioners: VCoP practitioners should pay close attention to how the structured flexibility of partnerships, design, and relationship development/accountability may promote or hinder VcoP’s continued evolution. Practitioners should shift perspective from short to mid- and long-term VCoP planning. Recommendation for Researchers: The new typology can stimulate further research to strengthen the clarity of language and findings related to VCoP functioning. Impact on Society: VCoPs are utilized by academic institutions, the private sector, non-profit organizations, the government, and other entities to fill gaps in adult learning at scale. The contextual implementation of findings from this study may impact VCoP design and drive improvements in opportunities for learning, global health, and well-being. Future Research: Moving forward, future research could explore how VCoP evaluations relate to different stages of learning, consider evaluation stages across the totality of VCoP programming design, and explore how best to capture VCoP (long-term) impact attributed to health outcomes and the culture of learning organizations and networks.

This paper aims to share the author's vision on possible research directions for big knowledge-based AI. A renewed definition of big knowledge (BK) and big knowledge systems (BKS) is first introduced. Then the first BKS model, called cloud knowledge social intelligence (CKEI) is provided with a hierarchy of knowledge as a service (KAAS). At last, a new semantics, the big-and-broad step axiomatic structural operational semantics (BBASOS) for applications on BKS is introduced and discussed with a practical distributed BKS model knowledge graph network KGN and a mini example.

Since the development of Open Educational Resources (OERs), different models regarding the usage of these resources in education have appeared in the literature. Wiley’s 4-Rs model is considered to be one of the leading models. Research based on Wiley’s model shows that using materials without making changes is the most common use. Compared to the extensive literature regarding OER usage in education, the literature barely deals with OER usage by instructional designers or training managers in corporations. The purpose of this research is to examine the OER usage of these two stakeholders, distinguishing between Little and Big OER repositories, in which Little OER repositories such as YouTube and Wikipedia aren’t necessarily designed to fulfill educational purposes. Findings show that these stakeholders almost use only Little repositories and that their usage level is higher than what is documented in the literature: they mostly Revise–modify the form of the resource, and Remix–combine different resources to create new ones. These differences can be explained by the fact that materials from Little OER repositories are raw materials, requiring further editing and adjustment. Significant differences between instructional designers’ and training managers’ usage of OERs were found regarding the Reuse level of resources from internal repositories and the Google Images repository, and the frequency of this Reuse.

Implementing inquiry in the outdoors introduces many challenges for teachers, some of which can be dealt with using mobile technologies. For productive use of these technologies, teachers should be provided with the opportunity to develop relevant knowledge and practices. In a professional development (PD) program in this design-based research, 24 teachers were involved in adaptation of a learning environment supporting inquiry in the outdoors that included the use of mobile technologies. They first experienced the learning environment as learners, then adapted it for their own use, and finally, enacted the adapted environment with peers. We examined the scope and character of teacher involvement in adaptation, and the consequent professional growth, by analyzing observations, questionnaires, interviews and the adapted learning-environments. Findings indicate that all teachers demonstrated change processes, including changes in knowledge and practice, but the coherence of the learning environments decreased when substantial adaptations were made. Some teachers demonstrated professional growth, as reflected by their implementation of ideas learned in the PD program in their daily practice, long after the PD program had ended. This study demonstrates how the Teachers as Designers approach can support teacher learning and illustrates productive use of scaffolds for teacher growth and professional development.

Creative computing is one of the rapidly growing educational trends around the world. Previous studies have shown that creative computing can empower disadvantaged children and youth. At-risk youth tend to hold a negative view of self and perceive their abilities as inferior compared to “normative” pupils. The Implicit Theories of Intelligence approach (ITI; Dweck, 1999, 2008) suggests a way of changing beliefs regarding one’s abilities. This paper reports findings from an experiment that explores the impact of a short intervention among at-risk youth and “normative” high-school students on (1) changing ITI from being perceived as fixed (entity view of intelligence) to more flexible (incremental view of intelligence) and (2) the quality of digital self-representations programmed though a creative computing app. The participants were 117 Israeli youth aged 14-17, half of whom were at-risk youth. The participants were randomly assigned to the experimental and control conditions. The experimental group watched a video of a lecture regarding brain plasticity that emphasized flexibility and the potential of human intelligence to be cultivated. The control group watched a neutral lecture about brain-functioning and creativity. Following the intervention, all of the participants watched screencasts of basic training for the Scratch programming app, designed artifacts that digitally represented themselves five years later and reported their ITI. The results showed more incremental ITI in the experimental group compared to the control group and among normative students compared to at-risk youth. In contrast to the research hypothesis, the Scratch projects of the at-risk youth, especially in the experimental condition, were rated by neutral judges as being more creative, more aesthetically designed, and more clearly conveying their message. The results suggest that creative computing combined with the ITI intervention is a way of developing creativity, especially among at-risk youth. Increasing the number of youths who hold incremental views of intelligence and developing computational thinking may contribute to their empowerment and well-being, improve learning and promote creativity.

This study examined a professional development program designed to support Civics teachers in their efforts to promote empathy among Israeli Jewish students towards Israeli Arabs. The design rationale for the program is that teachers should experience empathic processes themselves before supporting their students in such an endeavor and that meaningful empathic processes can occur online if activities are properly designed. All phases of the program were designed to support teachers to participate as part of an online community of practice. Sixty Jewish teachers participated in two iterations of the design study. Refinements were made in the second iteration to provide teachers with explicit definitions of empathy and specific instructions for reflection. Findings indicate that these changes were reflected in higher degrees of empathic responses among teachers. Teachers also indicated that being a part of an online learning community contributed to the learning process they experienced during the program. We interpret this as a first step in enabling teachers to assist their students to develop a more empathetic approach toward the minority group and conclude with a discussion of recommended design principles for promoting such an approach.

This paper identifies areas in the design science research (DSR) subfield of the information systems (IS) discipline where a more detailed consideration of practitioner audiences of socio-technical design artifacts could improve current IS DSR research practice and proposes an initial conceptualization of these audiences. The consequences of not considering artifact audiences are identified through a critical appraisal of the current informing science lenses in the IS DSR literature. There are specific shortcomings in four areas: 1) treating practice stakeholders as a too homogeneous group, 2) not explicitly distinguishing between social and technical parts of socio-technical artifacts, 3) neglecting implications of the artifact abstraction level, and 4) a lack of explicit consideration of a dynamic or evolutionary fitness perspective of socio-technical artifacts. The findings not only pave the way for future research to further improve the conceptualization of artifact audiences, in order to improve the informing power – and thus, impact on practice and research relevance – of IS DSR projects; they can also help to bridge the theory-practice gap in other disciplines (e.g. computer science, engineering, or policy-oriented sociology) that seek to produce social and/or technical artifacts of practical relevance.

The article presents Personal Knowledge Management (PKM) as an overdue individualized as well as a collaborative approach for knowledge workers. Designing a PKM-supporting system, however, resembles a so-called “wicked” problem (ill-defined; incomplete, contradictory, changing requirements, complex interdependencies) where the information needed to understand the challenges depends on upon one’s idea for solving them. Accordingly, three main areas are attended to. Firstly, in dealing with a range of growing complexities, the notion of Popper’s Worlds is applied as three distinct spheres of reality and further expanded into six digital ecosystems (technologies, extelligence, society, knowledge worker, institutions, and ideosphere) that not only form the basis for the PKM System Concept named ‘Knowcations’ but also form a closely related Personal Knowledge Management for Development (PKM4D) framework detailed in a separate dedicated paper. Reflecting back on a United Nations scenario of knowledge mass production (KMP) over time, the complexities closely related to the digital ecosystems and the inherent risks of today’s accelerating attention-consuming over-abundance of redundant information are scrutinized, concluding in a chain of meta-arguments favoring the idea of the PKM concept and system put forward. Secondly, in light of the digital ecosystems and complexities introduced, the findings of a prior article are further refined in order to assess the PKM concept and system as a potential General-Purpose-Technology. Thirdly, the development process and resulting prototype are verified against accepted general design science research (DSR) guidelines. DSR aims at creating innovative IT artifacts (that extend human and social capabilities and meet desired outcomes) and at validating design processes (as evidence of their relevance, utility, rigor, resonance, and publishability). Together with the incorporated references to around thirty prior publications covering technical and methodological details, a kind of ‘Long Discussion Case’ emerges aiming to potentially assist IT researchers and entrepreneurs engaged in similar projects.

This research aims to suggest key design characteristics that are necessary for developing usable e-commerce websites in the Arab world. A comprehensive usability evaluation of four leading Arab e-commerce websites was conducted using the heuristic evaluation method. The results identified major and minor usability problems and major and minor good design characteristics on the selected websites. Based on the results, 51 key design characteristics were suggested. The recommended key design characteristics comprised two levels according to their priority: level one which includes mandatory key design characteristics and level two which includes supplementary design characteristics. The key design characteristics in each level were categorized under specific pages and areas that can be found on any e-commerce website. Such categorizations could direct website evaluators and designers to important pages and areas that should be considered to improve the overall usability of e-commerce websites. The results of this research are particularly important to developing countries which are still facing challenges that may affect the design and accessibility of usable and useful websites. These relate to low speed of accessing the Internet and a lack of website designers who have experience in customers’ needs and websites’ usable design characteristics.

Aim/Purpose: Professional companies selling persuasive-communication services via the World Wide Web need to be exemplars of effective informing practices. Their credibility is at risk if their websites do not excel in marketing message and use of medium. Their unique brands need to be expressed through website technology and content, or they cannot compete successfully. Background: Compares marketing communication consultants’ websites with expert criteria. Methodology: Content analysis of 40 advertising agency websites. Contribution: Links an evaluation of advertising agency compliance with expert website criteria to established branding constructs. Findings: Most small advertising agencies could improve their brand reputations through better compliance with experts’ recommended website design and content criteria. Recommendations for Practitioners: A hierarchy of recommendations for practitioners is offered, addressing ease and importance. Impact on Society: Clarity and credibility of message and medium improve our ability to practice effective informing. Future Research: Explore online communications of specialized populations such as digital marketing experts.

Aim/Purpose: Personal Knowledge Management (PKM) has been envisaged as a crucial tool for the growing creative class of knowledge workers, but adequate technological solutions have not been forthcoming. Background: Based on former affordance-related publications (primarily concerned with communication, community-building, collaboration, and social knowledge sharing), the common and differing narratives in relation to PKM are investigated in order to suggest further PKM capabilities and affordances in need to be conferred. Methodology: The paper follows up on a series of the author’s PKM-related publications, firmly rooted in design science research (DSR) methods and aimed at creating an innovative PKM concept and prototype system. Contribution: The affordances presented offer PKM system users the means to retain and build upon knowledge acquired in order to sustain personal growth and facilitate productive collaborations between fellow learners and/or professional acquaintances. Findings: The results call for an extension of Nonaka’s SECI model and ‘ba’ concept and provide arguments for and evidence supporting the claims that the PKM concept and system is able to facilitate better knowledge traceability and KM practices. Recommendations and Impact on Society: Together with the prior publications, the paper points to current KM shortcomings and presents a novel trans-disciplinary approach offering appealing opportunities for stakeholders engaged in the context of curation, education, research, development, business, and entrepreneurship. Its potential to tackle opportunity divides has been addressed via a PKM for Development (PKM4D) Framework. Future DSR Activities: After completing the test phase of the prototype, its transformation into a viable PKM system and cloud-based server based on a rapid development platform and a noSQL-database is estimated to take 12 months.

Aim/Purpose: The growing complexity of the business environment and business processes as well as the Big Data phenomenon has an impact on every area of human activity nowadays. This new reality challenges the effectiveness of traditional narrowly oriented professional education. New areas of competences emerged as a synergy of multiple knowledge areas – transdisciplines. Informing Science and Data Science are just the first two such new areas we may identify as transdisciplines. Universities are facing the challenge to educate students for those new realities. Background: The purpose of the paper is to share the authors’ experience in designing curriculum for training bachelor students in Informing Science as a concentration within an Information Brokerage major, and a master program on Data Science. Methodology: Designing curriculum for transdisciplines requires diverse expertise obtained by both academia and industries and passed through several stages - identifying objectives, conceptualizing curriculum models, identifying content, and development pedagogical priorities. Contribution: Sharing our experience acquired in designing transdiscipline programs will contribute to a transition from a narrow professional education towards addressing 21st-century challenges. Findings: Analytical skills, combined with training in all categories of so-called “soft skills”, are essential in preparing students for a successful career in a transdiciplinary area of activities. Recommendations for Practitioners: Establishing a working environment encouraging not only sharing but close cooperation is essential nowadays. Recommendations for Researchers: There are two aspects of training professionals capable of succeeding in a transdisciplinary environment: encouraging mutual respect and developing out-of-box thinking. Impact on Society: The transition of higher education in a way to meet current challenges. Future Research The next steps in this research are to collect feedback regarding the professional careers of students graduating in these two programs and to adjust the curriculum accordingly.

Aim/Purpose: In a world of rapidly expanding complexity and exponentially increasing data availability, IT-based knowledge management tools will be needed to manage and curate available information. This paper looks at a particular tool architecture that has been previously proposed: The Personal Knowledge Management System (PKMS). The specific focus is on how the proposed architecture conforms to design science principles that relate to how it is likely to evolve. Background: We first introduce some recent informing science and design science research frameworks, then examine how the PKMS architecture would conform to these. Methodology: The approach taken is conceptual analysis. Contribution: The analysis provides a clearer understanding of how the proposed PKMS would serve the diverse-client ambiguous-target (DCAT) informing scenario and how it could be expected to evolve. Findings: We demonstrate how the PKMS informing architecture can be characterized as a “social machine” that appears to conform to a number of principles that would facilitate its long-term evolution. Future Research: The example provided by the paper could serve as a model future research seeking to integrate design science and informing science in the study of IT artefacts.

Aim/Purpose: To discuss the Design Science Research approach by comparing some of its canons with observed practices in projects in which it is applied, in order to understand and structure it better. Background: Recent criticisms of the application of the Design Science Research (DSR) approach have pointed out the need to make it more approachable and less confusing to overcome deficiencies such as the unrealistic evaluation. Methodology: We identified and analyzed 92 articles that presented artifacts developed from DSR projects and another 60 articles with preceding or subsequent actions associated with these 92 projects. We applied the content analysis technique to these 152 articles, enabling the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of activities performed and the types of artifacts involved. Contribution: The content analysis of these 152 articles enabled the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of the activities and types of artifacts involved. Evidence was found of a precedence hierarchy among different types of artifacts, as well as nine new opportunities for entry points for the continuity of DSR studies. Only 14% of the DSR artifacts underwent an evaluation by typical end users, characterizing a tenth type of entry point. Regarding the evaluation process, four aspects were identified, which demonstrated that 86% of DSR artifact evaluations are unrealistic. Findings: We identified and defined a set of attributes that allows a better characterization and structuring of the artifact evaluation process. Analyzing the field data, we inferred a precedence hierarchy for different artifacts types, as well as nine new opportunities for entry points for the continuity of DSR studies. Recommendation for Researchers: The four attributes identified for analyzing evaluation processes serve as guidelines for practitioners and researchers to achieve a realistic evaluation of artifacts. Future Research: The nine new entry points identified serve as an inspiration for researchers to give continuity to DSR projects.

Aim/Purpose: Developing Digital Platform Ecosystems (DPE) to transform conventional Knowledge Management Systems (KM/KMS) scenarios promises significant benefits for individuals, institutions, as well as emerging knowledge economies. Background: The academic entrepreneurship project presented is aiming for such a KMS-DPE configuration. Having consolidated this author’s own and external re-search findings, realization is currently commencing with a start-up in a business incubator. Methodology: Design science research applying mixed one-sample case study and illustrative scenario approach focusing on conceptual analysis and entrepreneurship. Contribution: Although (academic) entrepreneurship is a young research area with recently growing interest, publications focusing on this transitional stage between maturing research and projected commercial viability of digital technologies are rare. Findings: A roadmap looking beyond the immediate early-start-up perspective is out-lined by integrating recent development-stage-related DPE-research and by addressing stakeholders diverse informing needs essential for system realization. Recommendations for Practitioners and Researchers: As this transdisciplinary perspective combines KM, informing, design science, and entrepreneurial research spaces, it may assist other researchers and practitioners facing similar circumstances and/or start-up opportunities. Impact on Society: The article advances the understanding of how DPE communities may serve members with highly diverse skills and ambitions better to gainfully utilize the platform’s resources and generative potential in their personal and local settings. Future Research: As the entrepreneurial agenda will complement (not substitute) the academic research, research priorities have been highlighted aligned to three future stages.

To capture the complexity and diversity of systems with both technical and social features, modelling methods are needed that similarly provide various tools and concepts. Study of developed methods shows that despite all of their advantages and strengths, there is a need for a method that with a holistic approach integrates perspectives, strengths and tools of the developed methods and models with different aspects of socio-technical systems. The main aim of the current study is to design a method for modelling complex socio-technical systems. To achieve this goal, it is necessary to design a method that is based on creativity and existing knowledge base. Therefore, design science research is used as a research strategy to design proposed method. For the first time, design science research in the field of operations research has been used to design a modelling method. This study also presents new tools and concepts for modelling socio-technical systems.

After new ventures have exhausted the limited financial resources of founders, family, and friends, they often pursue initial external capital. To secure investment, entrepreneurs can signal about their venture's latent potential by aligning themselves with reliable third parties. Such affiliations affirm the new venture's legitimacy and provide substantive benefits in the form of mentoring, access to resources, and ongoing monitoring. However, early stage financing is an especially "noisy" signaling environment owing to the large number of startups seeking funding, many of which will not survive. The real value of third party affiliations in this context resides in their ability to unlock the potential of other more pedestrian signals, such as the entrepreneur's characteristics and actions that might otherwise go unnoticed. We borrow from the sensemaking literature to explain how third party affiliation signals disambiguate signals with multiple possible interpretations so that potential investors interpret them positively. Findings support our theory that a startup's characteristics and actions are signals that remain relatively unnoticed unless a startup combines them with a third party affiliation that enhances the signal's value, thus increasing the likelihood of receiving external capital.

This article extends the understanding of what impels buyers to contact particular sellers in online business-to-business (B2B) marketplaces, which are typically characterized by sparse social structures and concomitant limitations in observing social cues. Integrating an institutional perspective with signaling theory, our core argument is that offline seller characteristics that are visible online—in particular, geographic location and legal status—convey credible signals of seller behavior because they provide buyers with information on sellers' local institutional quality and the institutionally-induced obligations and controls acting on sellers. Using unique data from a large Italian online B2B marketplace between the fourth quarter of 1999 and July 2001, we find that both sellers' local institutional quality and their legal statuses affect a buyer's likelihood of contacting a seller. Moreover, consistent with the idea that a buyer's own local institutional quality generates a relevant reference point against which sellers are evaluated, we find that a buyer is progressively more likely to contact sellers the higher their local institutional quality relative to the buyer. Jointly, our findings imply that in online B2B marketplaces, signals conveyed by sellers' geographic locations and legal statuses may be substantive sources of competitive heterogeneity and market segmentation.

Labor codes have been voluntarily adopted and used by manufacturers in emerging economies for the past two decades, as a means of ensuring minimally acceptable or core labor standards for workers. However, far too little is known of the potential benefits from the voluntary adoption of labor codes to the manufacturer, and prior human resource management research has been virtually silent on the business implications of their use for emerging economy manufacturers participating in global supply chains. Drawing on previous work across multiple disciplines and proposing a framework that extends human resource management theory more explicitly and rigorously to the context of emerging economy manufacturing, I theorize and demonstrate that the voluntary adoption of a labor code may constitute an effective human resource investment in emerging economies in improving establishment-level employee outcomes and operational and financial performance. The hypotheses are tested using longitudinal data on a sample of apparel manufacturing plants in Sri Lanka. Implications of this study include providing insight into how to expand the scope and relevance of human resource management theory to better understand research and practice in emerging economies.