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This paper aims to identify different combinations of causal conditions (celebrity attributes) that explain our outcome: destination image. More specifically, three main research questions guide our work: (1) Which attributes should an outstanding sportsperson have to enhance the image of his/her country as a destination image? (2) Are these the same for different product categories? (3) Do tourists and residents differ?

To this end, the fuzzy-set Qualitative Comparative Analysis (fsQCA) was used with a sample of 187 participants (105 tourists and 82 residents).

Results show that some attributes of a sports celebrity are more critical than others in enhancing destination image. Those attributes of sports celebrities appearing in the intermediate and parsimonious analysis should be prioritized. This is the case of trustworthiness. Second, experience is a peripheral requirement (only appeared in the intermediate analysis). Third, attractiveness is unnecessary and an even and undesired attribute in many solutions. Fourth, when comparing tourists and residents, both groups value the role of football players, while residents also appreciate the role of marathon runners. Tennis players are the less relevant sports celebrities to build Spain’s destination image.

First, a new statistical analysis in the marketing discipline, QCA, has been used. The use of qualitative approaches to investigate destination images has been scarce. Second, the study of the role of sports celebrity endorsement on brand–place attachment has yet to be investigated. Third, studies about the role of residents in the image of a tourism destination/city are scarce. Tourists and residents must be investigated because they can benefit from sports celebrities' activities.

Fuzzy-set qualitative comparative analysis (fsQCA) is explored as a transformative tool rooted in complexity theory, shedding light on uncertainties shaping real-world decisions in tourism, with a focus on its application in the hospitality domain.

This study systematically evaluates fsQCA’s application in hospitality and tourism research, employing bibliometric analysis to scrutinize the published literature since its induction in 2011. The research seeks to understand the evolving usage by qualitatively reviewing impactful studies based on total citations.

The study reveals the ascendancy of fsQCA as a predominant approach in hospitality and tourism studies, particularly in illuminating decision-making paradigms in key sectors like destination and hotel selections and entrepreneurial orientations. However, an absence of fsQCA applications in gastronomy and wine tourism is identified, signaling uncharted territories for future inquiry.

Theoretical implications include paradigm shifts to complexity theory, configural analysis and asymmetric algorithms. Practical implications involve improved decision-making and tailored marketing, benefiting industry practitioners. Limitations include potential academic bias, while future research suggests exploring sub-sectors, sustainability and emerging technologies.

This study identifies gaps in the fsQCA application and pioneers its examination within the hospitality domain, offering a unique perspective on understanding intricate relationships and configurations among variables. The study emphasizes the efficacy of asymmetric methodologies in elucidating behavioral nuances in hospitality and tourism, providing a foundation for future inquiries to expand horizons and unravel the nuanced applications of fsQCA in this research domain.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

The purpose of this study is to investigate if a firm's exchange complexity profile (that is, the linkages between the firm and its environment) influences investor behavior at the negotiation table where a firm valuation is derived.

The authors utilize Qualitative Comparative Analysis (QCA). Specifically, the authors utilize fuzzy-set Qualitative Comparative Analysis (fsQCA), a QCA variant that allows the researcher to assign graduated membership in sets.

When the authors dichotomize their positions as either higher stakes that favor the seller (high capital, low equity, high valuation) or lower stakes that favor the buyer (low capital, high equity, low valuation), and when the authors focus primarily on the equity outcome, the authors find that investors adopt a reductionist stance that adheres to a transaction cost economics logic under conditions of lower stakes and higher complexity as well as higher stakes and lower complexity conditions. The authors interpret this to mean that equity serves as a counter-balancing lever for a firm's exchange complexity configuration.

On a theoretical level, the authors showcase the exchange complexity framework and differentiate its position within the extant frameworks that address a firm's competitive advantage. More generally, the authors note that this framework brings the discipline of micro-economics and the field of strategic management closer together, providing scholars with a new tool enabling research across industries for the portfolio level of analysis.

This paper aims to determine pathways leading to enterprise profitability during the COVID-19 pandemic in the Philippines.

The study (N = 272) was participated by 228 micro, small and medium enterprises (MSMEs) and 44 large enterprises. Configurational analysis using the fuzzy-set qualitative comparative analysis was used in modelling combinations of firm characteristics and organizational resilience attributes that could lead to enterprise profitability.

Using the Benchmark Resilience Tool of Resilient Organisations, the study showed that three main attributes of organizational resilience (leadership and culture, networks and relationships, and readiness to change) played significant roles in enterprise profitability. Other conditions of varying influence on profitability included costs, sales, number of employees and the number of years in operations of an enterprise. For MSMEs, profitability can be achieved if all resilience attributes are present, while for large enterprises, the absence of some resilience attributes can be compensated by other attributes such as low decline in sales, low employee reduction, and more years in operation.

While the COVID-19 pandemic’s impacts have been far-reaching, the MSMEs and large enterprises are more likely to be profitable if they have used the three organizational resilience attributes. Moreover, these attributes do not only improve firm profitability and the overall enterprise performance during the present pandemic but also prepare them for future shocks.

To the best of the authors’ knowledge, modelling antecedents of enterprise profitability using configurational analysis is the first in the Philippines.

As a response to global population growth and increasing demand for food, farmers have been complementing traditional agriculture practices with vertical farming (VF) and indoor hydroponic systems. To facilitate the growth of the VF industry, this paper aims to identify business model elements and their configurations that lead to high firm performance.

The research goals were met by conducting literature reviews coupled with a fuzzy-set qualitative comparative analysis (fsQCA) on five business model elements, “superior” OR “strong” performance as two possible outcomes, and the top-ranked global VF growers listed in the Crunchbase Database.

From the fsQCA results, it was observed that several business model configurations lead to strong firm performance. Vertical farms growing in urban settings and having strong customer engagement platforms, coupled with a presence of business-to-business (B2B) sales channels, are more consistently associated with superior performance. These results imply that the decision configuration of location, along with customer engagement activity and sales activity are differentiating factors between good firm performance and superior firm performance in the case of vertical farms.

This paper contributes to expanding the knowledge of business model theory, business model configurations and VF management, providing specific guidelines for vertical farm owners and investors related to decision-making for higher firm performance, as well as positive environmental, social and economic impact.

Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.

Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.

The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.

This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.

Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.

Trust is the glue that holds cooperative relationships together and often exists in an asymmetric manner. The purpose of this study is to explore how to mitigate the issue of losses or increased transaction costs caused by opportunistic behavior in a soft environment where trust asymmetry is quite common and difficult to avoid.

This study focuses on examining asymmetric trust between the government and the private sector in public-private partnership (PPP) projects. Drawing upon both project realities and relevant literature, the primary conditional variables influencing asymmetric trust are identified. These variables encompass power perception asymmetry, information asymmetry, interaction behavior, risk perception differences and government-side control. Subsequently, through the use of a survey questionnaire, binary-matched data from both the government and the private sector are collected. The study employs fuzzy-set qualitative comparative analysis (fsQCA) to conduct a configurational analysis, aiming to investigate the causal pathways that trigger asymmetric trust.

No single conditional variable is a necessary condition for the emergence of trust asymmetry. The pathways leading to a high degree of trust asymmetry can be categorized into two types: those dominated by power perception and those involving a combination of multiple factors. Differences in power perception play a crucial role in the occurrence of high trust asymmetry, yet the influence of other conditional variables in triggering trust asymmetry should not be overlooked.

The findings can contribute to advancing the study of trust relationships in the field of Chinese PPP projects. Furthermore, they hold practical value in facilitating the enhancement of trust relationships between the government and the private sector.

Considering corporate governance (CG hereinafter) practices' variety across Anglo-American and European countries, this study relies on contingency and complexity theories to investigate the effect of environmental sustainability performance (ESP hereinafter) on shareholder value under various configurations of board of directors (BoD hereinafter), firm and country characteristics.

The author used the Thomson Reuters Environment Pillar Score (ASSET4) and the Total Shareholder Return to assess ESP and shareholder value respectively. The author applied a fuzzy-set qualitative comparative analysis (fsQCA hereinafter) to an unbalanced panel of 2,284 observations from 486 European and Anglo-American non-financial listed firms over the period 2016–2020.

The author found a positive association between ESP and shareholder value and he displayed notable differences between Anglo-American and European economies regarding causal predictors of this positive association. Within European firms operating under civil law code where investor protection is low and family ownership is widespread, ESP creates shareholder value under configurations of causal predictors that significantly differ from those of their Anglo-American peers. The author's findings are robust to different identification strategies.

This study assists researchers, practitioners, shareholders and policymakers the significant roles that BoD diversity, organisational and institutional traits are jointly playing as determinants of the ESP-shareholder value relationship.

The author's study offers a more encompassing, complete and theoretically richer picture of the key drivers and outcomes of ESP.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.