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This study aims to examine the potential determinants of entrepreneurial intentions (EIs) among business students. To that end, the study investigates the role of entrepreneurship education (EE) and entrepreneurial passion (EP) (inventing and founding), as well as the mediating role of attitude towards entrepreneurship (ATE) and the moderating role of university support.

A close-ended questionnaire measured on a seven-point Likert scale was used to collect data from business students at nine universities in Punjab, Pakistan. The sample size comprises 377 participants who were selected using a stratified random sampling technique. Partial least square structural equation modeling (PLS-SEM) was then applied to assess the study’s model and the postulated hypothesis.

The findings indicated that (a) every independent variable (IV) directly impacts EI [dependent variable (DV)] except EP for founding (EPF), (b) ATE significantly mediates the relationship between IV and DV (c) perceived university support positively moderates the relationship between ATE and EI.

As an implication to policy, the Government must ensure that students are exposed to business environments and find university support through different paths. Specifically, Pakistan’s Minister of Education and the Higher Education Commission (HEC) may consider designing university programs that lead to more influential EE. The empirical findings may help policymakers develop effective policies for promoting entrepreneurship.

To meet customers' expectations on shorter lead times, high product availability, flexibility, and variation in delivery and return options, retailers have turned their attention to warehousing and are making big investments in technology. Currently, technology providers are pushing for smart warehousing, a new and under-researched phenomenon. This study aims to conceptualize the term and examine pathways toward implementing smart warehousing.

An exploratory survey was administered to 50 leading Swedish retailers in varying segments. A two-tailed t-test for equality of means was used to detect significant differences between current and future states.

The study found that future smart warehouses will be automated, autonomous, digital, and connected, but that retailers will follow different paths along this journey, driven by contextual trends, e.g. sales growth, wider product assortment, shorter lead-time offerings, and integration of brick-and-mortar and online stores. Interestingly, the study revealed that many of the retailers that aim to create smart warehouses in five years are not the retailers with the most developed technology today.

The paper operationalizes smart warehousing in two dimensions: degree of automation and degree of digitalization and connectivity of information platforms. Based on the findings, 16 theoretical propositions are put forth that, based on contextual factors, explain different pathways for retailers to implement smart warehousing.

The empirical insights and theoretical discussions provide practically useful guidance, including outlined trends, for selecting and benchmarking automation and complementary technologies in warehouse operations.

This paper conceptualizes and operationalizes smart warehousing – an original approach. It is also one of the first to investigate the technological transformation in retail warehousing empirically, explaining how and why retailers choose different pathways toward smart warehousing.

The study aimed to provide insights on antecedent and outcome of green HRM at the organisational level and the outcome of green HRM at the individual level. It also sought to examine the mechanism through which green HRM would lead to employees’ positive outcome.

A quantitative study design using a two-study approach was employed to collect and analyse the data. For study 1, 206 hotels from Malaysia were included in analysis at the organisational level, while in study 2 at the individual level, 508 employees from different sectors provided insights through an online questionnaire. For both studies, partial least squares (PLS–SEM) was used to assess the research model.

All the proposed hypotheses were supported. Specifically, at the organisational level, organisational environmental culture is positively related to green HRM, and green HRM management positively associates with organisation's environmental performance. At the individual level, green HRM positively influences employees' job satisfaction, and meaningfulness through work is a strong mediator in this relationship.

This study is significant as it contributes to both theory and practice by providing fresh insights on green HRM and its antecedent and outcomes at two levels (organisational and individual) and across two economies (emerging and developed). It also sheds some light on the outcome of green HRM at the employee level which is an area that is still under-researched. By focusing on meaningfulness through work as an important factor, the study contributes to better understanding of green HRM and employees’ positive outcomes.

India is a fast-growing economy, that has a majority share in the global information technology industry (IT). Rapid urbanisation and modernisation in India have strained its energy sector, which is being reformed to cope. Despite being the global IT heart and having above average research output in the field of artificial intelligence (AI), India has not yet managed to leverage its benefits to the full. This study aims to address the role of AI and information management (IM) in India’s energy transition to highlight the challenges and barriers to its development and use in the energy sector.

The study, through analysis of proposed strategies, current policies, available literature and reports, discusses the role of AI and IM in the energy transition in India, highlighting the current situation and challenges.

The results show dispersed research and development incentives for IT in the Indian energy sector; however, the needed holistic top-down approach is lacking, calling for due attention in this matter. Adaptive and swift actions from policymakers towards AI and IM are warranted in India.

The ongoing transition of the Indian energy sector with the integration of smart technologies would result in increased access to big data. Extracting the maximum benefits from this would require a comprehensive AI and IM policy.

The revolution in AI and robotics must be carried out in line with sustainable development goals, to support climate action and to consider privacy issues – both areas in India must be strengthened.

The paper offers an original discussion on certain applicable solutions regarding the energy transition of AI coming from the Global South; they are based on lessons learned from the Indian case studies presented in this study.

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.