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This paper aims to consolidate the state of research on information behaviour. Regardless of the scholarly surge on information behaviour using numerous models and extended ones, gaps still exist on the development of more pragmatic frameworks that explain and/or predict the information behaviour across different fragmented environmental situations. Therefore, this paper extends technology-organization-environment (T-O-E) framework and synthesizes different research positions into a multi-dimensional framework that assists small and medium enterprises (SMEs) to understand their information behaviour and to make informed decisions on the adoption of emerging information communication technology (EICT).

This study deployed an inductive approach; data were generated from unstructured and semi-structured interviews with 20 participants drawn purposively from Luton directories.

This study developed a more integrated framework underpinned by T-O-E framework, which helped to identify how EICT adoption is critically shaped by perceived information need, information sources selection and the factors determining information source selection.

Qualitative research is normally subjective, inductive, interpretive and limited on the sample used. However, because of the limited number of interviews used, as well as industry-specific nature of the study, the generalization of the framework and the findings will be difficult, hence, the need to test the framework on a broader population and cross-context testing.

The T-O-E framework is extended to Expectancy (T-O-E-E) to provide a more robust insight into information behaviour of SMEs from a multi-dimensional perspective. It also offers a more analytical framework for exploring critical issues identified and demonstrates the capacity to provide a reliable explanation to the findings. Further, it serves as a tool for assessing the benefits or challenges of SMEs information behaviour especially on the EICT adoption decision.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

The evaluation of time-based performance is a valued approach in the lean management thinking which is based on delivering value from customer's perspective. This approach contributes for long-term competitiveness and success in today's business environment. The focus of this study is to analyse the cycle time and manufacturing lead time with value stream mapping (VSM) in the preparatory stage of the textile fabric manufacturing process and to identify and improve the non-value adding activities in the value chain (VC). The study presents an insight on the translation of performance improvement across functions and how upstream supply chain (SC) segments can be linked in the performance improvement program. It also covers how the application of VSM improves visibility and planning flexibility in textile fabric manufacturing process.

The time-based performance was evaluated using VSM and recording of the activity times in the existing process. The impact of the quality of supplier's raw material was also measured contributing to identify the strategy for procurement and the means to establish a feedback system to the upstream segments of the SC. The methodology of VSM, observation of the practice and the expertise of the individuals involved with the process were utilised to develop the value stream maps and to identify value adding activities, non-value adding activities, existing gaps and plans for improvement.

The means for improving the time-based performance were identified and their impact was measured. The factors responsible for improvement are related to the production system and with the procurement strategy. The improvement was achieved in terms of available capacity utilisation, balancing the work flow in the preparatory stages, visibility of the process by measuring its capability and flexibility for the planning function. The study revealed that the effectiveness and enhancement of VSM and related tools should be adopted to address the issue of limiting success rates of long term and repeating application of such tools. Continuous improvement, innovations and the systematic embedding of VSM in the process life cycle provide the ways for achieving long-term success.

The paper presents a real and in-depth study on the application of VSM in the textile manufacturing process. The scope of the study is broad; it covers activities across functions with actual estimates of activity times in the manufacturing process for the focused value streams. It offers researchers the opportunity to analyse the translation of productivity improvement across functions and how upstream SC segments can be linked in a performance improvement program.

The study offers useful insight for the managers in textile manufacturing and other sectors for improving the time-based performance and achieving higher utilisation of capacity. It identified the production factors and their impact on warping and sizing cycle time in selected value streams and those which share common activities. It also identified the directions for future research when repeating the application of VSM in the continuous improvement cycle. Furthermore, since the industries need to progress towards advanced systems including Industry 4.0 standards, adoption of advanced VSM tool with relevant technology can align their production systems to develop the required capability. This will also bring a sustainable competitive advantage in the system.

The focused sector is stagnant in terms of productivity and innovation. The adoption of the advanced tools can facilitate the implementation of continuous improvement and innovation strategies.

The main focus of this study is to analyse and improve the cycle time in the preparatory stage of the fabric manufacturing process. This has impact on other important and tangible measures including capacity utilisation and work flow and intangible measures including production planning flexibility and process visibility. The improvement impact is across departments.

Integration between the different components of development is a major aspiration of the 2030 agenda, but the efforts of firms that intend to contribute simultaneously to multiple development trajectories may be hindered by trade-offs that occur between the different sustainable development goals (SDGs) and targets. At the same time, synergies may also materialize and reinforce firm’s contribution. This chapter analyzes the effects of multinational enterprises (MNEs) and other foreign investors on two different targets of SDG 7, namely access of population to modern energy systems, chiefly electricity, and the use of carbon-free and renewable energy sources in sub-Saharan Africa (SSA) countries, and the authors investigate whether foreign investors experience trade-offs and synergies in their contributions. A two-equation growth model of households’ access to electricity and carbon factor is estimated by employing a panel dataset that covers 15 SSA countries and foreign direct investment (FDI) from 82 origin countries over the 2005–2011 period. The findings reveal that foreign investors are subject to a trade-off in their effects, because when they foster access to electricity they are also likely to spur carbon factor increases, and vice versa, depending on the economic development of host and home countries. Nevertheless, electrification and carbon factor reduction are shown to be linked by a system-level synergy. The results have implications for the design of MNEs attraction measures and energy policy in recipient countries.

Given the lack of focus on a standardized measurement framework (e.g. benchmarking tool) to assess and quantify complexity within the supply chain, this study has developed a unified supply chain complexity (SCC) index and validated its utility by examining the relationship with firm performance. More importantly, it examines the role of firm owners' business knowledge, sales strategy and board management on the relationship between SCC and firm performance.

In this study, the unit of analysis is Indian manufacturing companies listed on the Bombay Stock Exchange (BSE). This research has merged panel data from two secondary data sources: Bloomberg and Prowess and empirically operationalized five key SCC drivers, namely, number of suppliers, the number of supplier countries, the number of products, the number of plants and the number of customers. The study employs panel data regression analyses to examine the proposed conceptual model and associated hypotheses. Moreover, the present study employs models that incorporate robust standard errors to account for heteroscedasticity.

The results show that complexity has a negative and significant effect on firm performance. Further, the study reveals that an owner's business knowledge and the firm's effective sales strategy and board management can significantly lessen the negative effect of SCC.

This study develops an SCC index and validates its utility. Also, it presents a novel idea to operationalize the measure for SCC characteristics using secondary databases like Prowess and Bloomberg.

The purpose of this study is to discover the factors related to human resource (HR) digital transformation (DT) in Bahrain during coronavirus disease 2019 (COVID-19) and to analyze the impact of e-human resource management (e-HRM) on organizational performance. These factors are funding, information technology (IT) infrastructure, technical support, digital skills or talents, organizational culture, employee resistance and top management support. These factors were tested to determine whether they affected HR DT in Bahrain during COVID-19. There are no findings in the researched literature regarding the proposed factors that affect HR DT in Bahrain during COVID-19 in this study.

For data collection, a quantitative method was applied by conducting an online survey and distributing it to HR executives and employees from multiple organizations in Bahrain, both in the private and public sectors.

This study proposes a DT adoption model based on seven factors extracted from the literature review. A questionnaire was deployed, and accurate data were collected, processed and then analyzed. The logit model shows determinants factor to the DT adoption where all variables have a positive effect.

Using technology in an organization’s HR practices, known as e-HRM or HR DT, is becoming more crucial since the COVID-19 pandemic. Unlike European countries, the HR sector in Bahrain is not prepared to adopt the e-HRM process. This paper proposes a model that enables the HR sector to adopt digital technologies. This model is based on the key factors that enable an effective transition to the sector’s digitalization (e-HRM). Future research is sought to provide additional insights into the same factors and measure their effect on HR DT during COVID-19 in other countries.

This study investigates entrepreneurial overconfidence (EOC) levels among solo entrepreneurs at the country level. Although transitions from solo to employer entrepreneur are relatively rare, the solo self-employed have become an important source of potential job creation by virtue of the sharp increase in their numbers in the past two decades. When EOC levels are too high, job creation ambitions may be unrealistic and unrealised. Unrealised ambitions and business failure can lead not only to psychological and financial costs for the individual entrepreneurs involved, but at the societal level also to wasted government resources, and increased costs for the entrepreneurial ecosystem as a whole. Therefore, it is important to know more about the entrepreneurial overconfidence levels of solo entrepreneurs in different countries and their determinants.

Using Global Entrepreneurship Monitor data for 71 countries over the period 2013–2016, the authors construct a new measure of entrepreneurial overconfidence of solo entrepreneurs and relate this to three recently developed indicators of national culture.

The findings indicate that EOC levels are positively related to Joy (versus Duty), and negatively related to Trust (versus Distrust). Finally, no significant relationship between entrepreneurial overconfidence and Individualism is found in the study (versus Collectivism).

Given the lack of literature examining the relationship between EOC levels and cultural variables hypotheses were developed using the existent body of knowledge in the area, which is at the early stage of development. The hypotheses derivation has used mostly theoretical arguments relating to the link between national culture and overconfidence of entrepreneurs in general, rather than relating specifically to solo entrepreneurs. The measure of EOC uses expectations of employment growth to proxy overconfidence, but other measures of entrepreneurial success may also be explored.

As the hiring of employees can be a costly process (Coad et al., 2017), it is important that entrepreneurs have realistic expectations of what it requires to hire employees. This is especially the case for solo entrepreneurs since they do not have experience of hiring their own employees. This paper addresses such issues at an aggregate level by exploring what factors explain country differences in overconfidence levels of solo entrepreneurs.

It is worthwhile to distinguish between solo and employer entrepreneurs when studying their EOC levels, as the ambitions of these two types of entrepreneurs are different. Empirically, this study introduces a new measure of EOC tailored towards the solo self-employed.

This study contributes to entrepreneurship literature by expanding current knowledge on entrepreneurial overconfidence at the country level. Past research has studied EOC at the individual level, however limited research exists on the phenomenon of EOC from a country level perspective. This is important as unrealised entrepreneurial ambitions may not only create substantial costs for the individual entrepreneurs involved, it may also lead to substantial societal costs, including waste of government resources.

The purpose of this paper is to introduce a double-stator switched reluctance machine (DS-SRM) for electric vehicles (EVs) and to propose multi-mode operations for this machine.

Analysis of flux linkage distributions and torque characteristics using finite element method (FEM). Building a dynamic simulation model based on electromagnetic characteristics, mathematical equations and mechanical motion equations of the DS-SRM drive system. The paper proposes multi-mode operations (inner-stator excitation mode, outer-stator excitation mode and double-stator excitation mode) based on motor working regions. It also conducts simulation and experimental results to verify the effectiveness of the proposed multi-mode operations strategies and control schemes.

There is almost no electromagnetic coupling between the inner and outer stators due to the specially designed rotor structure and optimized windings polarity configuration. Analysis of flux linkage distributions and torque characteristics verified the independence of inner and outer stators. Proposal of multi-mode operations and corresponding control rules achieved the smooth switching between different modes.

The paper introduced the DS-SRM for EVs and proposed multi-mode operations, along with control rules, to optimize its performance. The specially designed rotor structure, optimized winding polarity configuration, and the proposed multi-mode operations contribute to the originality of the research.

Original equipment manufacturers and other manufacturing companies rely on the delivery performance of their upstream suppliers to maintain a steady production process. However, supplier capacity uncertainty and delayed delivery often poses a major concern to manufacturers to carry out their production plan as per the desired schedules. The purpose of this paper is to develop a decision model that can improve the delivery performance of suppliers to minimise fluctuations in the supply quantity and the delivery time and thus maximising the performance of the supply chain.

The authors studied a single manufacturer – single supplier supply chain considering supplier uncertain capacity allocation and uncertain time of delivery. Mathematical models are developed to capture expected profit of manufacturer and supplier under this uncertain allocation and delivery behaviour of supplier. A reward–penalty mechanism is proposed to minimise delivery quantity and time of delivery fluctuations from the supplier. Further, an order-fulfilment heuristic based on delivery probability is developed to modify the order quantity which can maximise the probability of a successful deliveries from the supplier.

Analytical results reveal that the proposed reward–penalty mechanism improves the supplier delivery consistency. This consistent delivery performance helps the manufacturer to maintain a steady production schedule and high market share. Modified ordering schedule developed using proposed probability-based heuristic improves the success probability of delivery from the supplier.

Practitioners can benefit from the findings of this study to comprehend how contracts and ordering policy can improve the supplier delivery performance in a manufacturing supply chain.

This paper improves the supplier delivery performance considering both the uncertain capacity allocation and uncertain time of delivery.

This paper aims to investigate the relationship between oil price shocks and world food prices between 1974 and 2018.

The authors use the SVAR model to disentangle the oil price into supply, aggregate demand and oil-specific demand shocks and apply the detrended cross-correlations analysis to measure the association between oil price shocks and food returns/volatility and analyze contagion effects between oil and food markets.

The results show that the correlations between oil and food prices depend on whether oil prices changes are driven by supply or demand shocks. Particularly, food returns (volatility) are positively (negatively) more dependent on the oil price changes driven by aggregate demand (oil specific demand) shocks. Further analysis dealing with contagion analysis between oil and food markets shows a contagion effect during the food crisis of 2006–2008. Oil-specific demand shocks are the main source of this phenomenon.

This study differentiates itself from the previous literature by simultaneously disentangling oil price into supply, aggregate demand and oil-specific demand-driven shocks and evaluating the cross-correlations between each shock type and food returns/volatility. Specifically, this study has the originality of detecting the main source of contagion effects between oil and food markets over the food crisis of 2006–2008.

The results of this study are important for policymakers and investors. They should account for the oil price fluctuations differently depending on whether the oil price shocks are driven by the demand or supply side. Moreover, they should anticipate an increase (decrease) in food prices due to a positive (negative) oil shock. In addition, special attention should be accorded to the world oil demand. Finally, when a food crisis occurs, markets operators should focus more on the specific oil-demand shocks, as it is the most contributor to possible contagion effects between oil and food markets.

This study differentiates itself from the previous literature by simultaneously disentangling oil price into supply, aggregate demand and oil-specific demand-driven shocks and evaluating the cross-correlations between each shock type and food returns/volatility. Specifically, this study has the originality of detecting the main source of contagion effects between oil and food markets over the food crisis of 2006–2008.