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This paper aims to focus on data analytic tools and integrated data analyzing approaches used on smart energy meters (SEMs). Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency.

A few research strategies have been accounted for analyzing the raw data, yet at the same time, a considerable measure of work should be done in making these commercially reasonable. Data analytic tools and integrated data analyzing approaches are used on SEMs. Furthermore, while observing the diverse techniques and frameworks of data analysis of SEM, the authors propose a novel framework for SEM by using gamification approach for enhancing the involvement of consumers to conserve energy and improve efficiency. Advantages of SEM’s are additionally discussed for inspiring consumers, utilities and their respective partners.

Consumers, utilities and researchers can also take benefit of the recommended framework by planning their routine activities and enjoying rewards offered by gamification approach. Through gamification, consumers’ commitment enhances, and it changes their less manageable conduct on an intentional premise. The practical implementation of such approaches showed the improved energy efficiency as a consequence.

Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertainties in its application. This study aims to address this important issue by offering guidance regarding its use in contexts with which researchers struggle.

The authors examine the most prominent questions and answers posed in a well-known PLS-SEM discussion forum. The authors do so by using a text analysis technique to identify the most salient topics.

The data analysis identifies three salient PLS-SEM topics (i.e. bootstrapping and significance testing, higher-order constructs and moderation).

The results allow us to address the PLS-SEM community’s main methodological issues. The authors discuss each area separately and provide explanations and guidelines.

The guidelines on the most important PLS-SEM topics provide decision-making and application aids. In this way, the authors make a decisive contribution to clarifying ambiguities when applying the PLS-SEM method in hospitality management research and other disciplines.

There has as yet been no systematic analysis of this kind in the field of PLS-SEM; the authors, therefore, present the first research results. The findings and recommendations provide guidance for PLS-SEM applications in hospitality research and practice.

Based on resource-based and dynamic capabilities theorizing, this study explores how human resource analytics (HRA) can improve human resource management (HRM) performance and organizational performance, with creative problem-solving capability (CPSC) as an underlying mediator for creating value from HRA. It also explores how data quality and HRA personnel expertise act as moderators in this relationship.

Hypotheses are tested in an empirical study including 191 firms using partial least square structural equation modeling technique.

The findings confirm the direct and indirect effect of HRA use and maturity on HRM and organizational performance, as well as the mediating role of CPSC. HRA personnel expertise was found to moderate the relationship between HRA and CPSC, data quality being an important factor.

The findings contribute to the sparse evidence of value creation from HRA use/maturity on HRM and organizational outcomes, providing a theoretical logic of resource-based view and dynamic capabilities view based on the underlying causal mechanism through which HRA creates value. The study identified complementary capabilities which when combined with HRA use/maturity and CPSC result in value creation.

Pressure from competition; inflexible third-party reimbursements; greater demand from government, regulatory and certifying agencies; discerning patients; and the quest of healthcare entities for greater profitably place demands and high expectations for service quality impacting overall patient experience. Extending a prior multivariate, single-period model of varied medical practices predicting patient experience to a three-year time period to understand whether there was a change in overall assessment using data analytics. The paper aims to discuss these issues.

SEM was employed on a per year and aggregated, three-year basis to gain insights into qualitative psychometric constructs predicting overall patient experience and strength of the relationships.

Statistically significant differences were uncovered between years indicating the strength of the relationships of latent variables on overall performance.

Study focused on data gathered from a questionnaire mailed to patients who visited various outpatient medical clinics in a rural community with over 4,000 responses during the three-year study period. A higher percentage of female respondents over the age of 45 may limit the generalizability of the findings.

Practitioners can gain a broader understanding of different factors influencing overall patient experience. Administrative processes associated with the primary care provider are inconsequential. Patients are not as concerned with patient flow as they are with patient safety and health.

This research informs healthcare quality management of psychometrics and analytics to improve the overall patient experience in outpatient medical clinics.

The COVID-19 pandemic has caused havoc on a global scale for supply chains, which put forward higher demand for organizations to reassess their global supply chain strategy and improve supply chain sustainability. The purpose of this paper is to understand how leader's paradoxical cognition affect supply chain sustainability.

This study conceptualizes a research model grounded in upper echelons theory and propose a chain-mediating model under the moderating effect of big data analytics. Using PLS-SEM method, we test the hypotheses using survey data collected from supply chain managers or leaders of the supply chain team from 193 firms.

The results indicate that supply chain ambidexterity and organizational learning play a mediating role in the relationship between leaders' paradoxical cognition on supply chain sustainability, respectively, and these two variables have a chain-mediating role in the relationship above. In addition, the big data analytics negatively moderates the relationship between leader's paradoxical cognition and organizational learning, and further moderates our chain mediating model.

This research initiatively focuses on the micro-foundations of supply chain sustainability from managerial cognition and firstly provides empirical evidence about the impact of leader's paradoxical cognition on supply chain sustainability.

The purpose of this article is to provide an interview with the former web analytics guru, Marshall Sponder.

The paper provides an interview with Marshall Sponder, author of Social Media Analytics.

This special issue concludes with an interview with web analytics guru, Marshall Sponder. For over a decade, Marshall has been at the forefront of this growing field, influencing and advising large companies on how to determine ROI from their web‐based activity. His book, Social Media Analytics, proffers strategies for getting the most out of social media, as well as predicting the direction this field is likely to take in future, something Sponder is perfectly placed to do. In this interview he discusses at length the importance of a tactical approach to social media, the tools needed for measuring ROI, and emerging trends in social media.

The interview provides an insightful look at the emerging trends in social media analytics from the leading analyst in the field.

Leveraging the technology acceptance model (TAM) and the stimulus–organism–response (S–O–R) theory, this paper aims to investigate how the utilitarian and hedonic factors in virtual reality (VR) technologies affect consumers' intention to travel in the endemic phase of COVID-19. At the same time, the study incorporated emotional engagement and two forms of trust as possible organisms for this model.

Through snowball sampling, data collected from 263 respondents were analysed using the partial least square structural equation modelling (PLS-SEM).

The findings revealed that among the different forms of hedonic and utilitarian factors, all but perceived entertainment has a significant positive relationship to emotional engagement. Additionally, emotional engagement positively influences trust in the product and seller. However, the results show that only trust in the seller has a significant relationship with travelling intention. Predictive analysis shows that the model displays a strong predictive power.

This study differentiates from the existing literature by investigating the effect of VR technologies on the two different forms of trust and emotional engagement on travelling intention. This study extends earlier studies by supplementing the explanatory perspective with a predictive focus, which is particularly important in making sound recommendations on managerial decision-making.

Drawing on information processing view (IPV) theory, the objective of this study is to explore big data analytics (BDA) in pharmaceutical supply chain (PSC) for better business intelligence. Supply chain operations reference (SCOR) model is used to identify and discuss the likely benefits of BDA adoption in five processes: plan, source, make, deliver and return.

Semi-structured interviews with managers in a triad comprising pharmaceutical manufacturers, wholesalers/distributors and public hospital pharmacies were undertaken. NVivo software was used for thematic data analysis.

The findings revealed that BDA capability would be more practical and helpful in planning, delivery and return processes within PSC. Sourcing and making processes are perceived to be less beneficial.

The study informs managers about the strategic role of BDA capabilities in SCOR processes for improved business intelligence.

Adoption of BDA in SCOR processes within PSC is a step towards resolving the challenges of drug shortages, counterfeiting and inventory optimisation through timely decision. Despite its innumerable benefits of BDA, Australian PSC is far behind in BDA investment. The study advances the IPV theory by illustrating and strengthening the fact that data sharing and analytics can generate real-time business intelligence helping in better health care support through BDA-enabled PSC.

The purpose of this paper is to explore how resource recombination (RR) may be conceptualized with special reference to the competitiveness of Higher Education Institutions (HEI).

The paper consists of two main studies. Building on pertinent available literature on the subject area, a qualitative investigation was conducted with the help of a semi-structured interview guide. Findings of study one were systematically analysed against a literature derived template. Study two presents a quantitative survey investigation that follows from the codes and themes derived from study one. In study two, findings were validated and analysed with the help of structural equation modelling.

Study one findings identified a total of 64 individual themes representing resources (21 themes), business processes (29 themes) and complementary factors (14 themes), as elements of RR in HEI competitiveness. In study two, the measurement model for RR was found to contain five main factors, namely, asset, research and affiliation processes, automated technology management, financial support for HR and departmental initiatives mainstream staff rewards and retention and institutional brand image appeal.

A significant contribution is made to theory development in the area of RR. Other implications to HEI competitiveness in contribution to national development were offered.

The area of RR remains largely uncovered in strategic management. Conceptualizing RR in the context of HEI competitiveness is new and in the right direction to jumpstart interest in this area by proposing a validated measurement model of HEI.

The purpose of this paper is to investigate the role of trust management on the fundraising performance in reward-based crowdfunding.

A research model was constructed based on elaboration likelihood model (ELM) and literatures with five hypotheses developed. Data were collected from www.demohour.com - the first and one of the largest reward-based crowdfunding platforms in China. In total, 829 reward-based crowdfunding projects were analyzed to test hypotheses. To test the hypotheses, partial least squares was used to analyze data of entrepreneur/sponsor profiles, entrepreneur/sponsor behaviors, and crowdfunding projects.

Results indicated trust management significantly promoted fundraising performance via central (entrepreneur’s creditworthiness) and peripheral (entrepreneur-sponsor interactions) routes. The peripheral route (entrepreneur-sponsor interaction) showed significantly higher effects than the central route (entrepreneur’s creditworthiness). The finding aligns with authors’ assumptions derived from unique characteristics of reward-based crowdfunding – community and collaboration because personal, dynamic message interactions were more effective than static, historical success records on the trust establishment. In addition to the main effects, the results also showed entrepreneur’s prior success crowdfunding records positively moderated the effect of entrepreneur-sponsor interaction on fundraising performance.

This study is the first paper that reveals the value of trust management in reward-based fundraising, especially the effect of dynamic entrepreneur-sponsor message interactions. Entrepreneur-sponsor interactions not only promoted community benefits in crowdfunding, but also cultivated trust relationships between entrepreneurs and sponsors. Previous studies mainly focussed on the entrepreneur’s popularity level on third-party social media (such as Facebook) toward fundraising performance. This study examines the effect of direct entrepreneur-sponsor interactions on the crowdfunding platform. Additionally, this study found one moderating effect from the central route to the peripheral route. It is a rare case in studies based on ELM. Finally, this study demonstrates how to incorporate a theoretical framework guiding the analysis of structured and unstructured data for in-depth analysis, result interpretation, and corresponding intervention strategy development.