Transforming Capitalism for Sustainable Development: Achieving the Vision of Three Zeros

With a focus on the mediating roles of technological innovation and human capital development, this study examines how environmental, social, and governance (ESG) sustainability variables affect long-term economic growth in Ghana. The study is guided by the Human Capital Theory. The World Development Indicators (WDI) is the source of the secondary data used. The study adopted quantitative research design using partial least squares structural equation modeling (PLS-SEM) in examining the relationships between technological innovation, human capital development, economic growth, and ESG variables. According to the analysis, governance factors significantly affect Ghana's economic growth, whereas social and environmental factors have little discernible direct influence. However, the study revealed that technological innovation and the human capital development serve as indirect drivers of economic growth, underscoring the importance of these mediating variables in the Ghanaian context. The government of Ghana is advised to create governance frameworks, promote the incorporation of ESG principles into corporate operations, and allocate funds for technological innovation, healthcare, and education. Enhancing governance frameworks, incorporating social and environmental considerations into economic plans, and creating an environment that supports technological innovation should be top priorities for policymakers. By highlighting the critical role that governance plays in the economic development of developing countries, this study adds to the body of literature, the impact of ESG sustainability on economic growth in Ghana with human capital development and technological development as mediating factors.

Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)In view of its essential role in knowledge creation, multivariate data analysis prevails in the social sciences literature. The field of tourism is not an exception, specifically in the widely adoption of structural equation modeling (SEM), a multivariate technique, by tourism researchers over the past decade. While there are two major types of SEM including covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM), the former dominated previous tourism research. However, increasing use of PLS-SEM in tourism research has been witnessed in recent years. This upward trend is likely to persist in the near future given the growing popularity of PLS-SEM in other social sciences domains like marketing, strategic management, and management information system, as specified in the preface of the book. Indeed, PLS-SEM, in relative to CB- SEM, provides more flexibility in handling of data. For instance, PLS-SEM is well-suited for accommodating small sample sizes and complex model, fortesting a model containing both formative and reflective constructs, and for handling single-item measures. To this end, the timely introduction of the book A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) helps tourism researchers stand at the front edge of the SEM technique and make effective use of the PLS-SEM in data analysis. Additionally, the book illustrates the application of PLS-SEM with a free downloadable software namely SmartPLS which is essential to extend the application of PLS-SEM in tourism research.Authored by Hair, Hult, Ringo, and Sarstedt, the book consists of eight chapters. To equip the readers with the basic knowledge of PLS- SEM, Chapter 1 delineates the meaning of SEM and its relationship with multivariate data analysis, followed by a description of the major elements in multivariate data analysis. Then the basic elements of PLS-SEM are explained. Finally, PLS-SEM is distinguished from its counterpart namely CB-SEM while the major characteristics of PLS-SEM and the conditions where the PLS-SEM are more adequate than CB-SEM and vice versa are discussed. To step in the application of PLS- SEM, Chapter 2 firstly explicates the concepts in structural model specification including mediation, moderation, and higher-order models. Then specification of measurement model is explained with a special focus on the differences between reflective and formative measures. After that, the issues that need to be addressed after data collection are discussed. The chapter ends by creating the model in the SmartPLS is illustrated. With an established model, Chapter 3 focuses on model estimation. The chapter explains the algorithm underpinning the estimation and the statistical properties of the PLS-SEM method, as well as the options and parameter settings for running the algorithm. Following that, the issues about interpretation of results are explained. The final section illustrates the execution of model estimation in the SmartPLS.Based on the model estimation, empirical measures of the measurement and structural models are derived, where evaluation of the models takes place. Chapter 4 exhibits the major steps in model evaluation in the beginning. Thereafter, the chapter explains the evaluation of reflective measurement models according to three major criteria including internal consistency reliability, convergent validity, and discriminant validity, followed by an illustration with the SmartPLS. Chapter 5 explains the assessment of formative measurement models with respect to the criteria of convergent validity, collinearity, and significance and relevance of the formative indicators. The chapter also elucidates the basic concepts of bootstrapping which is used to examine the statistical significance of estimates in PLS- SEM. An illustration of the assessment of formative measurement model in the SmartPLS follows. Chapter 6 continues the topic on model evaluation by focusing on the assessment of structural model. …

Purpose In Ghana, the adoption and application of green building concepts and technologies have not been fully explored. The study aimed to look into the key barriers and how they affect this. Design/methodology/approach Purposive and snowball sampling techniques were used to select a total of 292 construction industry stakeholders in Ghana who provided information via a questionnaire survey used for the data collection. Exploratory factor analysis and Partial least squares structural equation modelling (PLS-SEM) were used for computing the data analyses. Findings According to the study findings, the top five most critical barriers to the uptake of green building concepts and technologies (GBCs and Ts) in Ghana are: lack of government incentives/supports for implementing green building technologies (GBTs), lack of knowledge and awareness of GBTs and their benefits, lack of GBTs databases and information, Lack of green building (GB) expertise/skilled labour and Higher costs of GBTs. Principal Component Factor Analysis was used to further analyse the data, which allowed for the reduction of the 27 (27) factors to just four (4) underlying critical barriers: (1) government and knowledge-associated barriers, (2) technical barriers, (3) cost and finance barriers and (4) stakeholders’ attitude barriers. PLS-SEM techniques were used to analyse this collection of barriers, and the results showed that stakeholders’ attitude-associated barriers and cost and finance-related barriers have a significant negative influence on the uptake of GBCs and Ts in Ghana. This study’s findings have provided empirical evidence of the critical barriers to the uptake of GBCs and Ts from all stakeholders. Stakeholders desirous of implementing GBCs and Ts would work against the negative influences on the uptake of GBCs and TS. Originality/value Although there has been an abundance of research to examine the critical barriers to GB, however, the uniqueness of this study is nested in modelling the influence of the barriers on the adoption of GBCs and Ts using the PLS-SEM path modelling.

PurposeStructural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including hospitality management. Although for many researchers, SEM is equivalent to carrying out covariance-based SEM, recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive alternative. The purpose of this paper is to systematically examine how PLS-SEM has been applied in major hospitality research journals with the aim of providing important guidance and, if necessary, opportunities for realignment in future applications. Because PLS-SEM in hospitality research is still in an early stage of development, critically examining its use holds considerable promise to counteract misapplications which otherwise might reinforce over time.Design/methodology/approachAll PLS-SEM studies published in the six SSCI-indexed hospitality management journals between 2001 and 2015 were reviewed. Tying in with the prior studies in the field, the review covers reasons for using PLS-SEM, data characteristics, model characteristics, the evaluation of the measurement models, the evaluation of the structural model, reporting and use of advanced analyses.FindingsCompared to other fields, the results show that several reporting practices are clearly above standard but still leave room for improvement, particularly regarding the consideration of state-of-the art metrics for measurement and structural model assessment. Furthermore, hospitality researchers seem to be unaware of the recent extensions of the PLS-SEM method, which clearly extend the scope of the analyses and help gaining more insights from the model and the data. As a result of this PLS-SEM application review in studies, this research presents guidelines on how to accurately use the method. These guidelines are important for the hospitality management and other disciplines to disseminate and ensure the rigor of PLS-SEM analyses and reporting practices.Research limitations/implicationsOnly articles published in the SSCI-indexed hospitality journals were examined and any journals indexed in other databases were not included. That is, while this research focused on the top-tier hospitality management journals, future research may widen the scope by considering hospitality management-related studies from other disciplines, such as tourism research or general management.Originality/valueThis study contributes to the literature by providing hospitality researchers with the updated guidelines for PLS-SEM use. Based on a systematic review of current practices in the hospitality literature, critical methodological issues when choosing and using the PLS-SEM were identified. The guidelines allow to improve future PLS-SEM studies and offer recommendations for using recent advances of the method.

PurposeGreenhouse effects and the need for cost savings necessitate that an organization's information technology (IT) managers design IT equipment acquisition and service provisioning policies to reduce carbon footprint and cost. Analyzing the influencing factors that influence stakeholders' attitudes toward adopting green information technology (Green-IT) is an important input in designing these policies. In essence, the research aims to investigate into the relationship between these factors and how they influence policy-makers' behavior in Nigerian manufacturing industries.Design/methodology/approachThe study develops a model based on the norm activation model (NAM) and the theory of planned behavior (TBP) to investigate the factors that influence decision-makers' intention in adopting Green-IT. A quantitative approach using a survey method is carried out to gather opinions of IT decision-makers using a random sampling technique. Partial least squares structural equation modeling (PLS-SEM) technique is applied to test the structural model and measurement model.FindingsThe study's findings support the use of the behavior model for Green-IT adoption. The study's finding indicates that subjective norms, perceived behavior control (PBC), manager's attitude, personal norm (PN), awareness of adverse consequences and the ascription of responsibility (AR) positively influence intention to adopt Green-IT.Research limitations/implicationsThe development and validation of the model are the study's theoretical contributions. The study reviewed the existing literature on the utilization of Green-IT to better understand the intention to adopt Green-IT in Nigeria. It added to the literature by identifying factors that can influence it as well as theoretical underpinnings that can fit the intentions of decision-makers. The scientific community and the industrial companies would have the chance to investigate how this integrated behavioral intention model promotes the use of Green-IT. The research predictors explained about 70.20% of the variance in the behavioral intention to adopt Green-IT.Practical implicationsResearch offers practical implications and recommendations for top management practitioners of the manufacturing industries. Business leaders can use the results of this study to develop an effective strategic IT policy for the successful adoption of Green-IT practices for enhanced productivity. The study found that decision-makers' Green-IT attitudes had a substantial impact on their behavioral intention to adopt Green-IT. The study highlighted the importance of the top management attitude toward green products to facilitate the adoption of Green-IT practices in manufacturing industries in Nigeria. Thus, the positive and significant attitude of policy-makers is a necessary tool toward the successful adoption of Green-IT. Therefore, to foster an environmentally sustainability friendly atmosphere, Nigeria's manufacturing industries shall strive to strengthen the decision-makers' attitude toward practicing Green-IT in their respective domains. The findings showed that AR, AQ, environmental concern (EC), perceived behavior and perceived behavior are critical factors to be considered in an organization.Social implicationsAccording to the findings, an individual's Green-IT attitude has a substantial impact on the environment as social behavior. As a result, the positive and essential attitude of the social sector is a key tool for efficient Green-IT implementation. Nigeria's social activists must try to create awareness campaigns to boost decision-makers' attitudes toward implementing Green-IT in their various regions to develop a friendlier environment. Thus, the identified factors can be of great help to the social sector in designing and implementing successful environmental-friendly policies that could support the adoption of Green-IT practices.Originality/valueThe current research look at Green-IT adoption in manufacturing industries of West African countries. The study offers practical implications and recommendations for top management practitioners of the manufacturing industries, government policy-makers and organizations to enhance the use of Green-IT for mitigating environmental degradation. Recommendations for future research are stated as concluding remarks.

Partial least squares structural equation modeling (PLS-SEM) is a multivariate statistical technique that helps examine complex relationships among a number of variables. Although its use has increased over decades, PLS-SEM remains underutilized in leisure research. The purpose of this methodological paper is to offer a primer on PLS-SEM for leisure researchers and to present a critical review of PLS-SEM’s strengths and limitations, while identifying potential applications of PLS-SEM across different sub-fields and theories in leisure research. Specifically, as to strengths, we discuss PLS-SEM’s sample size requirements, accommodation of formative and reflective measures, ability to model many variables and relationships, and statistical prediction capacity. In terms of its limitations, we review criticisms regarding PLS-SEM’s biased estimates as well as the lack of measurement error estimation and model fit assessment tools. Lastly, we provide recommendations for leisure researchers who wish to use PLS-SEM and journal editors and reviewers who assess PLS-SEM articles.

Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example

This study examines the impact of customer relationship management (CRM) practices and social media marketing (SMM) activities on customer retention among MSMEs in Aceh. It considers the dual role of social media in relationship management (CRM) and business engagement (SMM). Recognizing the widespread use of social media, the study explores different stages of its adoption and utilization in business. A formalized social media business profile is used as the moderating variable, defined by a firm's formal allocation of responsibility, outsourcing, funding, governance of social media, and broader changes to structure, processes, leadership, training, and culture. Data was collected from 565 MSMEs using questionnaires and analyzed with partial least squares structural equation modeling (PLS-SEM) and multi-group analysis. The results demonstrated a high predictive power of the model on customer retention. Within CRM, the findings indicated a significant difference in the effect of key customer focus on customer retention, with higher effects observed in MSMEs that do not formalize their social media business profiles. Additionally, technology-based CRM showed significantly higher effects on customer retention for those who formalize their social media profiles. Within SMM, the study revealed significant differences in the effects of customization and trendiness on customer retention, both of which were more pronounced in MSMEs without formalized social media profiles. Furthermore, word-of-mouth had a significantly higher impact on customer retention for MSMEs with formalized social media profiles. This research contributes theoretically by developing an integrated framework that identifies how key customer focus, CRM organization, knowledge management, technology-based CRM, customization, entertainment, interaction, trendiness, and word-of-mouth influence customer retention. It also explores the moderating effects of formalized social media business profiles on CRM practices and SMM activities within MSMEs.

The study investigates the relationship between green production, green technology, waste reduction, energy use, and sustainability. A Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was used for analysis. The data was collected from a sample of companies in the textile industry. The results suggest that green production and technology positively and significantly affect waste reduction and energy use, which mediates the positive relationship between these two factors and sustainability. This study concludes that green production and technology are critical drivers of sustainability and emphasizes the need to prioritize waste reduction and energy use in sustainable manufacturing practices. The study has practical and managerial implications in all production or manufacturing industries and provides a guideline for managers and policymakers to ensure sustainability.

PurposePartial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.Design/methodology/approachBased on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.FindingsThe use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.Research limitations/implicationsThis research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.Practical implicationsThe results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.Originality/valueThis is the first article to systematically review the use of PLS-SEM in the quality management discipline.

Index

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods for PLS-SEM are now readily facilitated by both open-source and commercial software packages. This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications. What makes the book unique is the fact that it thoroughly explains and extensively uses comprehensive Stata (plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM analysis. The book aims to help the reader understand the mechanics behind PLS-SEM as well as performing it for publication purposes. Features: Intuitive and technical explanations of PLS-SEM methods Complete explanations of Stata and R packages Lots of example applications of the methodology Detailed interpretation of software output Reporting of a PLS-SEM study Github repository for supplementary book material The book is primarily aimed at researchers and graduate students from statistics, social science, psychology, and other disciplines. Technical details have been moved from the main body of the text into appendices, but it would be useful if the reader has a solid background in linear regression analysis.

PurposeThis study’s goal is to research and describe developing green technology and green business models, as well as their commercial advantages. However, it focuses on how old business breakthroughs and models may be transformed into new green technologies and innovations that can affect the global business environment. This research concentrates on the technology component of green technologies and provides information on a variety of relevant emerging green business models and innovations such as energy efficiency, renewable energy consumption, commodities and systems, environmental protection, nontoxic materials, and waste minimization, among others. Additionally, this research connects Emerging Green Technology (EGT) innovations to the business for sustainability. It also emphasizes the advantages of green technology adoption in business specially in developing economies.Design/methodology/approachFor that purpose, a Systematic Literature Review (SLR) was performed based on the “inclusion/exclusion criteria” and “PRISMA flow diagram method”. The first screening and quality evaluation rejected 67 publications, 8 in eligibility and 10 in credibility. In the subsequent round, 45 papers out of 210 that met the search parameters were included to access the findings.FindingsThis study provides a foundation for future research into sustainable economic potential by examining the development, breakthroughs, obstacles, future trends and new research prospects of EGTs. As such, this research will serve as a helpful resource for economically growing nations looking to foster long-term growth in their businesses through sustainable development strategies.Research limitations/implicationsThe first limitation of the study is the generalization of the findings. The sample size of the study is limited. For that purpose, an SLR and “PRISMA flow diagram” methods were performed by “inclusion/exclusion criteria” for literature review. Except these, there are many new techniques of SLR. Further research with more sampling and sophisticated tests could produce better results for this study.Practical implicationsThis research provides valuable insights for businesses and politicians seeking to protect the environment, promote economic growth and create a sustainable society. The findings will be particularly useful for emerging nations grappling with issues related to technical innovation, safe environmental practices, reliable renewable energy sources, and ecological and economic growth.Originality/valueThis study’s findings will aid in the design and implementation of new green technology and innovations in current businesses, which will assist in limiting climate change and eventually affect their move to sustainable growth paradigms. For emerging nations, this study will be useful in addressing issues about technical innovation, safe environmental conditions, reliable renewable energy sources as well as ecological and economic growth. According to our research results, the authorities of developing nations would gain from utilizing green business models and technology to spur economic development. Our findings should thus add to the current body of knowledge.

PurposeThe purpose of this paper is to integrate the findings of articles appearing in European Journal of Marketing’s special section on covariance-based versus composite-based structural equations modeling (SEM).Design/methodology/approachThis is an editorial which uses literature review to draw conclusions regarding areas of agreement, areas for further research, and changing the discussion around composite-based SEM methods.FindingsThere are now four new areas of agreement regarding composite-based SEM. Researchers should adopt a toolbox approach to their methods and know the strengths and weaknesses of the research tools in their toolbox. Partial least squares (PLS) SEM and covariance-based SEM are not substitutes, and it is inappropriate to use the language of confirmatory factor analysis (CFA) in reporting measurement estimates from PLS SEM. Measurement matters and researchers need to devote effort to using reliable and valid multi-item measures in their investigations.Originality/valueThis postscript article outlines recommendations for authors, reviewers and editors regarding the analysis of data and reporting of results using structural equations models.

Our study explores the association between the adoption of green technology and the development of green dynamic capabilities to achieve green competitive advantage. This research concentrates explicitly on the mediating function of green product innovation. The study is grounded in the dynamic capabilities theory and seeks to improve understanding regarding how organizations can attain a competitive edge by employing green practices and capabilities. Data were obtained from 312 manufacturing business managers in Bangladesh. We utilized the partial least squares structural equation modeling (PLS-SEM) method to examine the data and evaluate the proposed hypotheses. The empirical evidence suggests that both green technology adoption and green dynamic capabilities significantly impact firms’ green product innovation and competitive advantage. Additionally, the findings indicate that green product innovation is a mediating variable in the association between green technology adoption-green competitive advantage and green dynamic capabilities-green competitive advantage. This research adds to the current body of literature by presenting empirical findings highlighting the crucial role of green technology and dynamic capabilities in promoting green competitive advantage. Our results reveal that it would be beneficial for organizations to prioritize adopting eco-friendly technologies and cultivating dynamic capabilities to improve their overall green performance. The present study contributes significantly to the literature by offering insights into the strategies managers and policymakers can employ to attain sustainable competitive advantage in the manufacturing sector.