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This paper aims to estimate the influence of HR practices and theories on organizational sustainability. The research also examines the role of innovation as a mediator among the relationship of HR practices and theories and organizational sustainability.

The research is based on the survey conducted among 386 employees of logistics firms across India. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) approaches were used for analysis. Approach proposed by Baron and Kenny (1986) was used to test the mediating effect.

The study finds that HR practices and theories have positive and significant influence on organizational sustainability. The research also reveals that after introducing innovation as a construct, it partially mediated the association of HR practices and theories and organizational sustainability.

The study inspects the extent to which innovation can acts as a mediator between the relationship of HR practices and theories and organizational sustainability in logistics sector in India, which has not been established in past studies.

This research aims to examine the influence of transformational leadership on employee efficiency. The research also examines the role of knowledge sharing as a mediator between transformational leadership and employee efficiency.

The research is based on the survey conducted among 200 employees of logistics firms. Exploratory Factor analysis (EFA) and Confirmatory Factor Analysis (CFA) approaches are used for the evaluation.

The study found that transformational leadership has positive and significant influence on employee efficiency. The research also demonstrates that after introducing knowledge sharing, it fully mediated the influence of transformational leadership on employee efficiency. The study suggests that, if leaders share their knowledge and expertise among the team, employees have a propensity to be highly effective and efficient than without knowledge sharing.

Blue collar staff and unskilled labors of the firms are not included in the study. So, the study is limited to white collar staff only which can further be expanded by considering other ground staff. Also few or no such researches have been conducted in logistics firms, particularly in Indian logistics firms. So, the result of this study can be used as reference to explore the area. This study can be replicated in the logistics firms of other regions also.

The finding of the study will help the top management of the organizations to formulate strategies to enhance its senior-subordinate relationship through knowledge sharing. The study also suggests that regular dissemination of knowledge among the team improves the efficiency of the team members and hence the performance of the organization.

This research examines the degree to which knowledge sharing acts as a mediator between transformational leadership and employee efficiency, which has not been found in previous studies.

This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.

Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.

As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.

Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.

The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.

This study aims to evaluate the effectiveness of substituting different concentrations of sesame, soy butter, dried moringa leaves and coconut powder on the physicochemical and sensory properties especially calcium and protein content of salted and sweet cookies.

Cookies were prepared by fortifying refined flour with sesame (T1 and T3) and soy butter (T2 and T4) and further fortified with dried moringa leaves (salted) and coconut (sweet). Linear programing was used to formulate percentage of major ingredients to yield maximum calcium and protein. Cookies were evaluated for physical, textural, colour, nutritional, functional and organoleptic properties and compared with refined flour cookies, C1 (salted) and C2 (sweet).

It was observed that fortification significantly decreased the hardness of the test cookies when compared with control. C2 cookies were observed to be the hardest (42.3 N), whereas T2 cookies were the softest (23.7 N). Nutritional and functional components of fortified (T) cookies were significantly (p = 0.01) higher than control (C) cookies, and within T cookies, salted cookies were more nutritious than sweet cookies. Cookies fortified with sesame and dried moringa leaves (T1) contained the highest protein (19 g), calcium (312 mg) and flavonoids (2.0 QE mg/100g) content. Scores on sensory acceptability revealed that T cookies were highly acceptable when compared to cookies for all sensory attributes tested.

Incorporation of protein and mineral rich natural ingredients like sesame, soy butter, dried moringa leaves and coconut powder has improved the nutritional, functional and sensory properties especially calcium and protein content of salted and sweet cookies. There is tremendous scope for utilisation, commercialization of such plant-based nutrient dense ingredients in variety of food snacks, and this will ensure better nutritional security.

Fortification of biscuits with sesame, soy butter, dried moringa leaves and coconut powder resulted in to a superior quality of biscuits in terms of its protein, minerals specially calcium, flavonoid content and organoleptic acceptability. These protein and calcium rich biscuits may help in solving many nutritional deficiencies and can add variety to the bakery industry.

ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by exploring teachers' perspectives on the adoption of ChatGPT, with a focus on identifying factors that motivate and inhibit them to adopt ChatGPT for educational purposes.

This research has employed a interpretative phenomenological analysis (IPA) qualitative approach. Through in-depth interviews among the teachers, data will be collected to identify the motivating and inhibiting factors that impact teachers' willingness to adopt ChatGPT. The data was collected from 34 teachers working across 10 branches of the University of Technology and Applied Sciences (UTAS) in Oman.

The analysis revealed four themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purpose. These include Theme 1: Exploration of innovative education technologies, Theme 2: Personalization teaching and learning, Theme 3: Time-saving and Theme 4: Professional development. On the other hand, inhibiting factors includes five themes which includes Theme 1: Reliability and accuracy concerns, Theme 2: Reduced human interaction, Theme 3: Privacy and data security, Theme 4: lack of institutional support and Theme 5: Overreliance on ChatGPT.

This study contributes to the understanding of teachers' perspectives on the adoption of ChatGPT in education. By understanding teachers' perspectives, policymakers can design appropriate policies and service providers can customize their offerings to meet teachers' requirements. The study's findings will be valuable for higher education institutions (HEIs) in formulating policies to ensure the appropriate and effective utilization of ChatGPT. The study will provide suggestions to ChatGPT service providers, enabling them to focus on motivating factors and address inhibiting factors, thereby facilitating the seamless adoption of ChatGPT among teachers.

In comparison to previous studies, this study goes beyond merely discussing the possible benefits and limitations of ChatGPT in education. This research significantly contributes to the understanding of ChatGPT adoption among teachers by identifying specific motivating and inhibiting factors that influence teachers to adopt ChatGPT for educational purposes. The research enables to gain important new insights that were not previously found, giving a fresh dimension to the existing literature.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this study aims to explore the factors influencing educators’ acceptance and utilization of chat generative pretrained transformer (ChatGPT) in the context of higher educational institutions. This study additionally examines the moderating influence of trust on the association between intention and adoption of ChatGPT.

A structured questionnaire was disseminated to 1,214 educators following the purposive sampling method. The hypothesized relationships between the extended UTAUT model constructs and ChatGPT adoption were examined using structural equation modeling.

The results of this study indicate positive impact of ChatGPT adoption and its use behavior (UB) among educators. Performance expectancy, effort expectancy, hedonic motivation, facilitating conditions and habit have a positive impact on behavior intention to use this tool among educators in higher education institutions, However, the educators intend to use ChatGPT in a personal capacity and are negatively influenced by the social groups. Moreover, behavior intention to adopt ChatGPT has a larger effect on the UB due to the higher involvement of trust.

This research adds to the literature on technology adoption by emphasizing the significance of trust in the adoption of emerging technologies, such as big language models. This study’s findings have implications for ChatGPT technology developers, legislators and academics considering the implementation of ChatGPT for teaching and research.

This research investigates ChatGPT adoption among higher education educators using the UTAUT model. It emphasizes the role of trust in adoption, highlights key adoption factors and reveals a paradox: educators are personally inclined to use ChatGPT but hesitant due to negative social influence. This study's novelty lies in its focus on trust and its implications for developers, legislators and educators, offering valuable insights for integrating ChatGPT in education.

Government employees have various challenges of adopting e-government which include administrative problems, technological challenges, infrastructural problems, lack of trust on computer applications, security concerns and the digital divide. The purpose of this paper is to identify the most salient factors that influence the employee adoption of e-government in India as perceived by government employees involved in e-government service delivery.

The paper first identifies different factors influencing the employee adoption of e-government on the basis of literature review and then finds their relative importance by prioritizing them using the analytic hierarchy process (AHP). The AHP is a multi-criteria decision-making (MCDM) tool which combines all the factors into a hierarchical model and quantitatively measures their importance through pair-wise comparisons (Saaty, 1980). Eleven influencing factors of employee adoption of e-government have been identified, which are categorized under four main factors, namely, “employee’s personal characteristics”, “technical factors”, “organizational factors” and “trust”. The data pertaining to pair-wise comparisons of various factors and sub-factors related to the study is collected from ten senior government employees working with different departments and bodies of the Government of National Capital Territory of Delhi.

Based on the results obtained, the findings reveal that “organizational factors” and “technical factors” are the two most important factors which influence the intention of government employees to adopt e-government. Moreover, “training”, “technical infrastructure”, “access speed”, “technical support” and “trust” in infrastructure are the top five sub-factors which are considered to be important for the employee adoption of e-government.

One of the limitations regarding the methodology used in the study is that the rating scale used in the AHP is conceptual. There are chances of biasing while making pair-wise comparisons of different factors. Therefore, due care should be taken while deciding relative scores to different factors. Also, some factors and sub-factors selected, for the model may have interrelationships such as educational level and training; computer skills and trust; etc., and these interrelationships are not considered by the AHP, which is a limitation of the present study. In that case, the analytic network process (ANP) can be a better option. Therefore, this study can be further extended by considering some other factors responsible for e-government adoption by employees and applying the ANP in the revised model.

The results of the study may help government organizations, to evaluate critical factors of employee adoption of e-government. This may help them in achieving cost-effective implementation of e-government applications by efficiently managing their resources. Briefly, the findings of the study imply that government departments should provide sufficient training and support to their employees for enhancing their technical skills so that they can use the e-government applications comfortably. Moreover, the government departments should also ensure fast access speed of the e-government applications so that the employees can carry out their tasks efficiently.

Most of the existing literature on e-government is focused on citizens’ point of view, and very few studies have focused on employee adoption of e-government (Alshibly and Chiong, 2015). Moreover, these studies have majorly used generic technology adoption models which are generally applicable to situations where technology adoption is voluntary. As employee adoption of e-government is not voluntary, the present study proposes a hierarchy of influencing factors and sub-factors of employee adoption of e-government, which is more relevant to the situations where technology adoption is mandatory. Also, most of the previous studies have used statistical methods such as multiple regression analysis or structural equation modelling for examining the significant factors influencing the e-government adoption. The present study contributes to this area by formulating the problem as an MCDM problem and by using the AHP as the methodology to determine the weights of various factors influencing adoption of e-government by employees.

The discussion about using Chat Generative Pre-Trained Transformer (ChatGPT) by teachers is making notable progress on a daily basis. This research examines the teachers' adoption intention to adopt ChatGPT by focusing on perceived trust and perceived risk. The study seeks to elucidate the impact of these two factors on teachers' adoption intentions towards ChatGPT.

This study was exclusively conducted at private higher educational institutions in Gujarat, India. Data collection was done through a cross-sectional survey design. The proposed conceptual model was examined with the help of structural equation modelling (SEM).

The outcome of the study confirms the significant contribution of perceived usefulness, perceived ease of use, perceived trust, perceived intelligence, perceived anthropomorphism and social influence to teachers' intention to adopt ChatGPT. The findings of the study show that perceived risk exerts a negative moderating effect between perceived usefulness and adoption intention as well as between perceived trust and adoption intention.

This study fills the knowledge gap about teachers’ adoption of ChatGPT at private higher education institutions, thus contributing to the existing literature. Specifically, the distinctive role of key variables like perceived risk and perceived trust helps increase the existing body of knowledge.

Several practical implications are presented on the basis of the conclusions from the outcome of the study that would help increase teachers’ adoption intention of ChatGPT in higher education institutions. These implications include recommendations to promote the integration of ChatGPT in educational set-ups to help teachers leverage its potential benefits into their teaching practices.

This research study goes deeper into the subject than previous research, which mainly focused on the possible advantages and downsides of ChatGPT applications in the field of education. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers for educational purposes by investigating through the lens of perceived risk and perceived trust. The study offers fresh understandings that were previously ignored and brings new perspectives to the body of literature.

The metaverse represents a rapidly evolving digital environment that blurs the lines between physical and virtual reality, and it offers unique opportunities and challenges for businesses and marketers. The purpose of this study is to provide a comprehensive review of metaverse marketing research. The present study reviews the literature on metaverse to identify theories, contexts, gaps and methodologies using TCCM framework (Theories, Contexts, Characteristics and Methodology) to set a future research agenda.

A review was conducted of 179 English papers related to metaverse marketing from 2010 to 2023 from the Scopus and Web of Science core collection after applying relevant filters using the TCCM framework.

The findings suggest that the studies have inadequately distinguished metaverse as something that only builds interactive experiences that combine the virtual environment and the real world, whereas the theoretical domain of metaverse is dominated by studies in various domains. The applicability of metaverse marketing research is pertinent in various domains of the management field. The study explores various facets of metaverse marketing to capture its dynamic nature.

By presenting a comprehensive review, themes and knowledge gaps of the research on metaverse marketing, this study will enhance research output and provide valuable tools for future research on metaverse.

By analyzing metaverse in marketing, the companies will be able to use this concept effectively to formulate innovative marketing strategies and personalized consumer experiences and understand consumer behavior. Furthermore, research into metaverse marketing will be helpful in offering predictions about future trends in consumer behavior, technology adoption and virtual world development.

This study provides a thorough analysis of the current state of research on metaverse in marketing and provides a road map for further research in this area.