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The purpose of studying digitization transformation of the supply chain is to understand how digital technologies and processes are changing the way supply chains operate and to identify the opportunities and challenges associated with this transformation. Studying digitization transformation of the supply chain is important because it can help global businesses in identifying the best practices in supply chain management (SCM) systems and enhance supply chain performance. Hence, this research study is contributing in revealing the outcomes of digital inclusiveness in overall SCM for the growth of retail and e-commerce based platforms.

This research is using both descriptive and explanatory research designs to provide a comprehensive understanding of the problems in SCM. Descriptive research provides a detailed description of the characteristics of the population under study, while explanatory research identifies the causal relationships between the variables. Descriptive research has helped us to develop hypotheses about the relationships between variables that can be tested using explanatory research. Explanatory research has been used to validate the findings of descriptive research. By using both descriptive and explanatory research designs, our research design has increased the generalizability of our findings.

According to this study, businesses intend to change their supply chain strategies after the wake of competitive era to make them more robust, sustainable and collaborative with suppliers, customers and stakeholders by investing more in SCM technology like Blockchain, AI, analytics, robotic process automation and data control centers. This study evaluates the impact of digitization on supply chain systems. This includes assessing the benefits of digitization and identifying the factors that contribute to successful implementation. This research is studying the role of data analytics in SCM and how it can be leveraged to improve efficiency, reduce costs and increase transparency.

The study highlights the importance of adopting digitization in supply chain systems to improve supply chain robustness, sustainability and collaboration with stakeholders. This study's emphasis on data analytics in SCM presents an opportunity for businesses to gain insights into their supply chain systems and make data-driven decisions. This can enhance efficiency, reduce costs and improve overall supply chain performance. The study's focus on SCM technology and data analytics may overlook other factors that contribute to successful SCM, such as organizational culture, human resources and supply chain governance.

This study will complement to the existing body of information, management theory and practice and will benefit all. The research work is original and can be implemented worldwide to promote digitization in SCM for smooth transactions in the entire chain of wholesalers, retail distributors and customers.

This study aims to examine the use of the metaverse in tourism and hospitality to comprehend better how the technology might shape customer journey management, especially relative to information provision, experiences and customer benefits.

This explanatory research used a two-stage approach of media analysis and practitioner interviews to analyse the interactions among tourism information provision, customer experiences and customer benefits in the metaverse. It conceptualized and mapped the consumer journey of the emerging metaverse experience, focusing on the ideas and practices of metaverse design pioneers in tourism and hospitality.

Based on the media analysis and interviews with 27 designers, the metaverse – information – experiences – benefits (MIEB) model was proposed, containing three parts (information characteristics, customer experiences and customer benefits) and 31 supporting items grouped into nine components.

One of the unique contributions of this research is the MIEB model for applying the metaverse in customer journey management (pre-, during- and post-trip). The findings contribute to the current literature with this model based on the practical perspectives of metaverse designers and provide insights on how to incorporate the MIEB model in applying the metaverse in tourism and hospitality management. The findings also address existing literature gaps of insufficient research on metaverse management and design through all stages of the customer travel journey and by paying attention to stakeholders’ viewpoints, including the media and designers of metaverse applications. Engaging in semi-structured interviews with pioneers of the metaverse to gain insights into the design of tourism experiences was also different from other metaverse tourism research, although this is not claimed as a significant point of innovation.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

This study aims to investigate the effect of financial satisfaction (FS) on customer loyalty in the banking industry.

The study followed an explanatory research design using responses from 334 respondents from commercial banks in Tanzania. A stepwise regression analysis was used to validate the relevance of the study model.

The results indicate a positive and statistically significant association between customer loyalty and FS with levels of assets (β = 0.598, p < 0.001), savings (β = 0.186, p < 0.001) and debts (β = 0.065, p < 0.001). Of the three dimensions of FS, the level of assets had the strongest contribution to customer loyalty, followed by the level of savings and debts, in that order.

The study used a model of FS that was linked to customer loyalty in the Tanzanian banking industry. It is recommended that the model be tested in other environments to increase the generalizability of the findings.

This study provides an alternative way for banks to strengthen customer loyalty by enhancing FS.

The FS model (Joo and Grable, 2004) and the social exchange theory (Blau, 1964) are used in this study to propose a model of customer loyalty in the banking industry. Customer loyalty and FS have not been connected in prior studies.

The authors examine the effect of supply chain resilience (SCR) on supply chain performance (SCP) while considering the moderating effect of supply chain network complexity (SCNC) on the nexus between SCR and SCP of manufacturing firms.

The quantitative research approach and explanatory research design were utilised for this study. A sample of 345 manufacturing firms in the Accra metropolis was drawn. The partial least square structural equation modelling was employed.

Findings from the study revealed that SCR has a significant positive effect on SCP. However, SCNC had a significant negative moderating effect on the relationship between SCR and SCP.

The authors advocate that manufacturing firms are prone to stronger impact from complex networks that mitigate the already existing positive relationship between SCR and SCP and is dependent on the context in which the study is executed, and the extent to which resilience strategies are robust. Thus, the SCNC has an adverse impact on how well partners interact and how well the supply chain functions.

This is the first study that quantitatively investigates the SCR impact on SCP in the presence of SCNC of manufacturing firms in the context of a developing economy. The study redefines SCNC from earlier studies.

The study aims to investigate the impact of anxiety and depression (dimensions of mental health) on mineworkers' safety behaviors (safety compliance and safety participation) while examining the moderating role of safety climate on these relationships.

A quantitative research approach with an explanatory cross-sectional survey research design was adopted. A total of 274 purposively selected mineworkers participated in the study. Responses were obtained from participants through a structured questionnaire which was analyzed using the partial least square structural equation modeling.

Anxiety had a significant negative effect on safety compliance but not participation. However, depression was found to have a significant negative effect on both mineworkers' safety compliance and participation behaviors. The findings of the study also show that safety climate moderates the relationships between the dimensions of mental health and mineworkers' safety behavior except for the relationship between anxiety and mineworkers' safety participation behavior.

The study offers an account of the negative effect of mental health on mineworkers' safety behavior whiles highlighting that safety climate is an important construct to mitigate the negative effects of mental illness on the safety behaviors of mineworkers.

This study aims to examine authentic leadership behavior (ALB) and empowering leadership behavior (ELB) as predictors of innovative work behavior (IWB) while assessing the mediating role of work-family enrichment (WFE).

Through the explanatory research design, data was retrieved from 303 respondents from 16 small-sized hotels in Ghana and analyzed quantitatively using descriptive and inferential statistics (hierarchical component analysis within PLS-SEM).

The study’s findings revealed that both ALB and ELB positively and significantly relate to IWB. Additionally, our study found that WFE partially mediated the nexus between ALB and IWB as well as ELB and IWB.

The findings of our study imply that in the pursuit of excellence, ALB and ELB in the hospitality industry are crucial, as they not only nurture employee potential but also help employees to thrive both at home and at the workplace.

The hospitality literature lacks a comprehensive understanding of the underlying mechanism by which ALB and ELB influence IWB. To the best of the authors' knowledge, our study is the first empirical study conducted on ALB, ELB, WFE, and IWB in the hospitality industry.

This paper aims to investigate the impact of halal awareness on the relationship between halal supply chain knowledge and purchase intention for halal meat products in the millennial generation.

The quantitative approach with the respondents of 177 millennial generations in Indonesia is selected to understand the relationships between variables. Structural equation model-partial least square is used to analyze the relationship between variables.

The findings of this study found that the purchase intention of halal products in the millennial generation is influenced by several factors such as halal supply chain knowledge, halal certification and logo and religious beliefs. However, the results of this study also show that concern for halal products failed to moderate the relationship between these three main variables on the purchase intention of halal products.

This study provides insights into the concern that strengthens the relationship between the main variables on the intention to purchase halal meat products for the millennial generation.

The COVID-19 pandemic necessitated a significant shift in how employees executed their professional responsibilities. Concurrently, the incidence of cybercrime experienced a noteworthy surge due to the increased utilisation of cyberspace. The abrupt transition to telecommuting altered the interpersonal dynamics inherent in traditional work environments. This paper aims to examine the impact of interpersonal factors on the cybercrime preventative measures adopted by telecommuting employees.

A conceptual model, grounded in the Theory of Interpersonal Behaviour, is evaluated through an online survey. The data set comprises responses from 209 employees in South Africa, and the analysis uses partial least squares structural equation modelling.

The results reveal substantial predictive power to explain cybercrime preventative behaviours. Notably, the study underscores the significant influence of habit and affect on intention and subsequent behaviour.

The results suggest that practitioners should give due attention to emotional dimensions (affect) as a catalyst for information security behaviour. The formulation of employees’ information security responsibilities should be pragmatic, fostering subconscious compliance to establish routine behaviour (habit).

This research underscores the pivotal roles played by habit and emotions in shaping behavioural patterns related to information security. Furthermore, it provides researchers with an illustrative model for operationalising these constructs within the realm of security. The results contribute additional perspectives on the repercussions of the COVID-19 pandemic on cybercrime preventative behaviours.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.