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Recent studies have highlighted the importance of adopting a contingency approach to configuring omnichannel warehouses. Nonetheless, research on how various contextual factors influence the selection of warehouse configuration is scarce. This study fills this knowledge gap by exploring how and why certain configurations fit in different omnichannel contexts.

A case study is conducted with six leading Swedish omnichannel retailers. Focusing on outbound warehouse configurations, data are collected through interviews, on-site observations, and secondary sources. A multistep analysis is made, including both pattern matching and explanation building.

The qualitative analysis reveals 16 contextual factors, of which assortment range, requested online order fulfillment times, goods size and total transactions are the most influential. The study shows how contextual factors create different challenges, thereby influencing the choice of the configurations. In addition to market dynamics and task complexity, the study describes four categories of the factors and related challenges that are particularly important in omnichannels: speed, space, economies of scale and tied-up capital.

The findings highlight the importance of understanding context and imply that multiple challenges may require trade-offs when selecting configurations, for example, regarding what storage, processes and resources to integrate or separate. To confirm, extend, challenge and further operationalize the ideas and observations put forward in this paper, an agenda with future research issues is given for this accelerating, contemporary phenomenon.

Managers could leverage the frameworks proposed for the contextual profiling of their current and future positions. The frameworks provide support for understanding the important challenges and potential trade-offs and developing aligned configurations.

This study is original in the way it provides in-depth, case study findings about contextual factors and their influence on omnichannel warehouse configuration.

Due to the global labor market challenges, international companies react and adjust fast to these circumstances by implementing digital solutions into all business processes. Organizational ambidexterity is seen as the response of digital transformation and it can be divided into structural, contextual, and sequential dimensions. In this context, organizations representing the smart industry will need employees with specific competencies which let them meet technological challenges.

This chapter aims to clarify the state of opinion on expectations towards, and preparedness for, the impact of Industry 4.0 on human resources management and the implementation of various types of ambidexterity in these companies. We have conducted interviews with key HR informants from manufacturing companies operating in Germany and Poland. We have found that Industry 4.0 has a significant impact on HR practices. In both international companies, various digital solutions in employee recruitment, development, and performance, have been implemented. There have also been mature examples in both companies of structural, contextual, and sequential ambidexterity.

Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re-contextualization in knowledge retrieval.

This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies.

The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously.

Because of the chosen case study approach for validation, the validation results may lack generalizability.

The scheme enables an informed selection of KMSs appropriate for a particular OMIS use case, as the scheme’s attributes serve as design rationale for a certain architecture or constellation of components. Developers can not only select from various approaches when designing re-contextualizaton but also come up with rationales for each candidate because of structured representation. Hence, stakeholders can be supported in a more informed way and design KMSs more effectively along organizational change processes.

The paper addresses an identified need for systematic characterization of KMS approaches and systems intending to meet the objectives of OMISs. As such, it allows streamlining further research in this field, as approaches can be judged according to their originality and positioned relative to each other.

Project managers face decisions every day and those decisions result in an “either or” situation. This is also true when it comes to the choice of a project management approach, i.e. predictive versus iterative. A case is made in this article that project managers should be ambidextrous and apply practices that are beneficial to the project, irrespective of the origin of the practices.

This study is based on a questionnaire focussing on six themes. The results of 290 projects were analysed using ANOVA and boxplots to test for skewness and variances.

Based on the analysis of 117 practices, most of these projects could be classified as either hybrid or iterative projects. The results indicate that irrespective of the classification of the projects or the industry, projects are managed using a hybrid approach, with a tendency to incorporate more iterative practices than predictive practices.

This article contributes to the current debate on which approach is the best given certain circumstances.

This paper investigates how to embrace an “either/and” logic, borrowed from the Yin-Yang epistemological system, to provide a different perspective to the entrepreneurial orientation (EO) research and reframe its paradoxes and dilemmas.

The study adopts the duality map for paradox management, a tool designed to recognize and measure the threshold as a range within which opposite elements can be properly balanced for a healthy tension, to show that the apparently contradictory poles of the EO construct can co-exist within the same organization depending on specific situations, contexts and time.

By using duality maps as working models, the study shows that, in real life, the apparently contradictory poles of the EO construct co-exist in a healthy tension within the same organization and are managed in a constant process of dynamic balancing over time.

The present paper contributes to the EO research by providing a different perspective to the EO concept, thus filling the gap on how to go beyond the traditional polarized (“either/or”) paradigm that has dominated the EO literature since its origins.

EO is dominated by a polarized view that sees opposites as sharp dichotomies. However, the complexity and variability of today’s interconnected world are pushing scholars to move from this hegemonic Western perspective by adopting different cultural and philosophical approaches able to balance the inherent duality of the EO concept.

The purpose of this paper is to examine innovative practices and emphasize the mechanism of knowledge transfer across knowledge boundaries. By comparing and discussing the emerging boundary issues in knowledge transfer among small- and medium-sized enterprises (SMEs) registered in the incubation centers in China, this paper identified the main knowledge transfer approach and several contextual and organizational factors impacting knowledge transfer.

The authors conduct 39 semi-structured in-depth interviews with employees working within business incubation centers in China. The study uses thematic analysis for data analysis.

Our results contribute to the literature of knowledge transfer and in particular to our understanding of boundary conditions and knowledge transfer approaches in emerging economies. The results also highlight several contextual and organizational factors which impact knowledge transformation across the pragmatic boundary in the context of China.

First, organizations need to establish an effective process with tools to accommodate novelty; second, organizations should be aware of the impact of entrepreneurial orientation on innovative performance; and third, it will help organizations if they adopt and integrate information-rich media in managing innovative practices.

This research highlights the impact of contextual and organizational factors of SMEs on knowledge transfer in emerging markets and chooses incubation centers as study subjects, which is an organizational context that has not been thoroughly studied due to its unique nature and emerging complexity.

The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of computer science education.

This study adopted the quasi-experimental design to determine the efficacy of the CTCA in breaking difficulties related to the study of spreadsheets as a difficult concept in the Nigerian computer science education curriculum. Junior high school students studying computer science education participated in the study. The control group had 30 students, with 35 students in the experimental group. The experimental group was taught using CTCA, while the control group used the lecture method. The spread sheet achievement test, which had 40 items on spreadsheet, was used to collect data.

The results showed that the experimental group significantly outperformed the control group [F (1,60) = 41.89; p < 0.05]. The findings showed the potential of CTCA in improving students' performance in spreadsheets in the computer science education curriculum.

The originality of this study is hinged on its ground-breaking test of the CTCA to the study of the spreadsheet. The findings of this study indicate its efficacy in improving students' understanding of spreadsheet and computer science education.

Many recommender systems are generally unable to provide accurate recommendations to users with limited interaction history, which is known as the cold-start problem. This issue can be resolved by trivial approaches that select random items or the most popular one to recommend to the new users. However, these methods perform poorly in many cases. This paper aims to explore the problem that how to make accurate recommendations for the new users in cold-start scenarios.

In this paper, the authors propose embedded-bandit method, inspired by Word2Vec technique and contextual bandit algorithm. The authors describe user contextual information with item embedding features constructed by Word2Vec. In addition, based on the intelligence measurement model in Crowd Science, the authors propose a new evaluation method to measure the utility of recommendations.

The authors introduce Word2Vec technique for constructing user contextual features, which improved the accuracy of recommendations compared to traditional multi-armed bandit problem. Apart from this, using this study’s intelligence measurement model, the utility also outperforms.

Improving the accuracy of recommendations during the cold-start phase can greatly raise user stickiness and increase user favorability, which in turn contributes to the commercialization of the app.

The algorithm proposed in this paper reflects that user contextual features can be represented by clicked items embedding vector.

This study aims to present a step-by-step implementation of the culturo–techno-contextual approach (CTCA) in a university classroom to teach industry and competitive analysis in the Ghanaian undergraduate entrepreneurship development curriculum. It further investigates the efficacy of the CTCA in breaking difficulties related to the study of industry and competitive analysis as a difficult concept in the Ghanaian entrepreneurship development curriculum. In doing this, the CTCA is compared with the lecture method.

The study adopts a quantitative approach. A quasi-experimental design is employed to gather data from 215 level 400 (4th-year undergraduate students) entrepreneurship development students at a Ghanaian public university. The experimental group was taught with CTCA, while the control group used the lecture method. The data was collected using the industry and competitive analysis achievement test (ICAAT). As random assignment to experimental and control groups were not possible, the data were subjected to an analysis of covariance approach with pre-test scores added as a covariate.

The results show that the experimental group significantly outperformed the control group. The results further indicate the efficacy of CTCA in improving undergraduate students’ performance in complex concepts of entrepreneurship.

Researchers usually test alternative teaching methods to break down barriers to study difficulties. The study’s uniqueness stems from the CTCA’s ground-breaking application to the study of entrepreneurship development in a Ghanaian public university.