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Given the sudden increase in plant investments across the manufacturing sector due to recent disruptions in the global supply chain caused by the COVID pandemic, the Ukraine/Russian war, ocean piracy incidents, and others, there is a need to strategically align the investments decisions with the overall business strategy. This study aims to establish whether strategic alignment enhances the effect of plant investments on operational performance.

Using the fifth version of the Global Manufacturing Research Group (GMRG V) dataset, we employ a structural equation model (SEM) to establish the moderating role of strategic alignment in plant investments-operational performance relationships.

The results suggest that strategic alignment enhances the positive effect of plant investments on operational performance, especially in cost, delivery, flexibility, and innovation. However, we found partial support for the moderating role of strategic alignment on quality performance.

Although the study was based on the GMRG global dataset and numerous papers have been published using the same dataset, the use of a convenience sample on a select group of companies may limit the generalizability of the results. With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

The study comprehensively demonstrates that the extent of improvement in operational performance depends on how closely plant investment decisions align with the overall company strategy. Manufacturers should align major investment decisions with competitive priorities driven by market requirements to enhance operational performance.

Due to white rice’s association with diabetes and other chronic diseases in many Asian countries, many industries are working to develop high-fiber rice substitutes with similar organoleptic characteristics. Konjac rice (KR) is a promising option, but maintaining its optimal fiber content for health benefits while preserving its ideal sensory profile remains a challenge. This study aims to investigate whether a KR formula, combining tapioca flour and glucomannan gel, possesses similar organoleptic attributes to white rice while preventing glycemic response elevation.

In a six-week randomized single-blind clinical trial, 13 normoweight nondiabetic subjects received varying konjac-based rice and white rice ratios. Blood glucose levels were measured at intervals, and glycemic response was assessed using incremental area under the curve (iAUC). Visual analog scale gauged satiety, and organoleptic properties were evaluated.

Substituting white rice with pure and partial konjac-based rice significantly lowered postprandial blood sugar levels and glycemic response (p = 0.002). iAUC for pure KR and KR 1:1 was notably lower than white rice (p = 0.002). Subjects reported a sense of fullness comparable to white rice, with no significant organoleptic score differences (p = 0.260).

The study’s generalizability is compromised due to the limited number of participants, impacting external validity. The examined parameters offer a rough understanding of konjac grain’s impact on postprandial glycemic responses but do not elucidate underlying mechanisms or the duration of its inhibitory effect on glucose absorption. Long-term effects on metabolic, hormonal parameters and the colon’s microbial flora composition and function remain unexplored, constraining comprehensive insights into konjac grain’s extended implications.

This study introduces a novel KR formula to address the escalating diabetes risks associated with white rice consumption. Substituting white rice with KR significantly reduces postprandial blood sugar levels, highlighting its potential in preventing type 2 diabetes (T2D). Tapioca flour enhances palatability, making KR a viable option. While promising, long-term effectiveness and safety require further research, emphasizing comprehensive lifestyle interventions. The study contributes valuable insights to innovative dietary strategies for prevalent health conditions, emphasizing the need for ongoing efforts in public health.

White rice, a staple in Asian societies, is linked to a heightened risk of T2D due to increased production and inadequate dietary fiber. This connection contributes to the economic burden on governments through health insurance and lost productivity. Encouraging alternatives rich in fiber can mitigate this burden, offering a socioeconomically beneficial solution to preventable chronic diseases.

This trial demonstrates konjac-based rice’s potential in curbing glycemic responses, hinting at its role in preventing T2D. Glucomannan’s viscosity, satiety induction and potential gut health impact are highlighted. Further research is warranted for long-term effectiveness and safety. These findings contribute to the growing evidence supporting glucomannan as a valuable tool in addressing prevalent health conditions.

Previous studies emphasized the substantial energy-saving potential of light emitting diode (LED) lighting systems, especially in the clothing industry. However, the specific quantification of energy conservation potential in industrial factories, particularly in Bangladesh’s readymade garment (RMG) sector, remains unexplored. The purpose of this study is to investigate the potential energy savings and efficiency improvements of lighting systems in Bangladesh’s RMG sector using LED technology.

Understanding and optimizing energy consumption is crucial in the RMG sector because this sector contributes significantly to the country’s export earnings. For this, an RMG factory was surveyed and possible lighting system retrofitting was estimated and compared.

The adoption of energy-efficient lighting options, particularly LED, could decrease the current lighting energy usage from 15% to 7.5% in Bangladesh. First, this study reveals, that the reduction of annual energy consumption was determined to be 18,220 kWh due to the retrofitting of the lighting system with LED tube. Second, it conducts real-time measurements to assess the suitability of in-building lighting systems, providing insights into the current scenario. Lastly, it evaluates the economic and environmental benefits of the proposed lighting system in the RMG industries. Due to the retrofitting of the lighting system, the reduction of equivalent CO₂ gas emissions was found to be 119.896 tCO₂.

For the first time, this study explored the potential for enhancing energy-efficient lighting system design through retrofitting in the RMG industry, with a focus on Bangladesh. By addressing these aspects, this study aims to contribute to the advancement of energy efficiency and conservation efforts in the RMG sector, ultimately fostering sustainable industrial development in Bangladesh and beyond.

Online fundraising has become a rapidly growing alternative business financing method for esports. Despite this, a lack of attention has been given to its fans' motivations for participating in crowdfunding (CF) projects or behavioral intentions for spectatorship. To address this, the present study (1) categorizes esport CF investors' motivations based on the big five personality traits and (2) compares whether motivations and behavioral intentions for esports spectatorships vary depending on each group.

We applied K-means clustering analysis to classify investors. ANOVA was used to verify whether there were differences in CF motivations and behavioral intentions.

The study identified six distinct investor segments. Overall, esports CF investors showed high agreeableness and conscientiousness with low neuroticism. Fanatic fans were the most motivated and had the highest spectatorship intentions, driven by strong openness. In contrast, recognition seekers and charity donors exhibited the lowest viewing intentions. Entertainment seekers were highly motivated by excitement and aesthetics, linking CF participation to a strong desire to watch events. Despite higher neuroticism, reward hunters also showed significant viewing intentions, driven by drama and aesthetics. These findings highlight the diverse motivations and their influence on esports spectatorship.

This study investigates the motivations and behavioral intentions of CF investors and spectatorship, which has substantive theoretical and managerial implications for the business of esports.

Companies increasingly leverage artificial intelligence (AI) to enhance human performance, particularly in e-commerce. However, the effectiveness of AI augmentation remains controversial. This study investigates whether, how and why AI enhances human agents’ sales through a randomized field experiment.

This study conducts a two-by-two factorial randomized field experiment (N = 1,090) to investigate the effects of AI augmentation on sales. The experiment compares sales outcomes handled solely by human agents with those augmented by AI, while also examining the moderating effect of agents’ experience levels and the underlying mechanisms behind agents’ responses.

The results reveal that AI augmentation leads to a significant 5.46% increase in sales. Notably, the impact of AI augmentation varies based on agents’ experience levels, with inexperienced agents benefiting nearly six times more than their experienced counterparts. Mediation analysis shows that AI augmentation improves response timeliness, accuracy and sentiment, thereby boosting sales.

This study highlights the role of AI augmentation in human–AI collaboration, demonstrates the varying impacts of AI augmentation based on agents’ experience levels and offers insights for organizations on how to regulate AI augmentation to enhance agent responses and drive sales.

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.

This study examines why long-term relationships between expert users and smart voice assistants (SVAs) develop. It postulates that the five dimensions of experience (i.e. sensory, affective, intellectual, behavioural and relational) generate feelings of love for SVAs. The formation of love is examined considering three components: passion, intimacy and commitment. These feelings encourage users to continue employing and to generate long-term relationships with SVAs.

Data from a survey of 403 USA expert users of SVAs provide the input for structural equation modelling.

The results show that three dimensions of experience influence users’ passion towards SVAs: affective, intellectual and behavioural. Moreover, passion can convert the effect of users’ experiences into intimacy and commitment. Finally, intimacy and commitment increase users’ intentions to continue using SVAs.

The findings obtained make three original contributions. First, this study is the first to analyse expert users of SVAs and the post-technology adoption stage. Therefore, it introduces a new case of relational marketing in smart technologies. Second, this study contributes by applying a new theoretical perspective that evaluates the importance of users’ experiences with SVAs. Third, it takes an interpersonal approach to explore user-SVA interactions, revealing that users can develop human-like love feelings for SVAs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0570

This study aims to investigate the impact of technological turbulence on entrepreneurial orientation (EO) in Chinese e-commerce enterprises. It also examines the mediating roles of business ties and political ties, and the moderating effect of transaction uncertainty on these relationships.

A sample of 173 Chinese e-commerce enterprises was analyzed using survey data. Structural equation modeling was employed to test the proposed hypotheses, including the direct effects of technological turbulence on EO, the mediating roles of business and political ties, and the moderating effect of transaction uncertainty.

The results indicate a positive correlation between technological turbulence and EO. Business ties mediate the relationship between technological turbulence and EO, while political ties do not. Transaction uncertainty negatively moderates the relationship between business ties and EO but does not significantly affect the relationship between political ties and EO. Additionally, EO positively impacts market performance.

This study extends the understanding of how external environmental factors, such as technological turbulence, influence EO in the context of Chinese e-commerce. It highlights the differential roles of business and political ties and provides insights into the moderating effects of transaction uncertainty. The findings offer practical implications for e-commerce firms seeking to enhance their entrepreneurial capabilities in turbulent environments.

Today, the transition of retailers from multi-channel and cross-channel to omni-channel has become a necessity. Customers’ perceived shopping value is also one of the most important factors for retailers’ success. Therefore, the purpose of this paper is to develop and validate the omni-channel shopping value scale.

Based on 40 interviews (X = 18, Y = 22) and a literature review, items were generated for shopping value dimensions (utilitarian, hedonic and social) at four touchpoints. Then exploratory factor analysis was performed for scale purification (n = 562). Confirmatory factor analysis (CFA) was performed (n = 528) for initial scale validation. A second CFA was conducted to validate the final scale (n = 302). To check the nomological validity of the scale, the effect of omni-channel shopping value on customer engagement (n = 455) was investigated in both generations.

According to the results of the qualitative study, 73 items were identified. Based on the results of exploratory and CFA, nine components (50 items) were extracted and confirmed: utilitarian, hedonic and social shopping values for offline touchpoint and utilitarian and hedonic shopping values for online, application and social networks touchpoints. The results of nomological validity of the scale confirmed the effect of omni-channel shopping value on customer engagement in both generations.

To the best of the authors’ knowledge, this study is the first attempt to develop and validate an omni-channel shopping value scale based on customers’ shopping experiences with omni-channel brands. Therefore, this study provides a useful tool for researchers and marketing managers to measure omni-channel shopping value.

This study aims to (1) investigate the influence of firms’ social media utilization on performance through supply chain agility, (2) examine the mediating role of supply chain agility and (3) explore the indirect effect of social media utilization on operational performance via supply chain agility as knowledge transfer increases.

A survey of 298 Chinese manufacturing firms was conducted to assess the proposed relationships, employing moderated mediation analysis with Andrew Hayes (2017) PROCESS macro.

Social media utilization indirectly enhances operational performance through supply chain agility, supporting our mediation hypothesis (H1). Additionally, knowledge transfer moderates the positive impact of social media utilization on supply chain agility (H2). The moderated mediation analysis reveals that the mediating effect of supply chain agility on operational performance is stronger at higher levels of knowledge transfer (H3), shedding light on the intricate relationships between these variables and providing insights for businesses seeking to leverage social media and knowledge transfer to enhance supply chain resilience and operational performance.

This study empirically investigates the role of social media utilization in supply chains within the digital age. We explore how social media enhances supply chain agility and knowledge transfer, highlighting its transformative potential for real-time communication, responsiveness and collaboration across networks. By integrating dynamic capability theory with contemporary digital practices, we demonstrate how leveraging digital platforms alongside traditional supply chain processes can significantly improve manufacturing efficiency. This research bridges existing gaps in the literature and provides valuable insights for businesses navigating complex, rapidly changing environments in the era of digital transformation.