Analysis Of Necessary Conditions Research Articles

Unravelling the nice-to-have and must-have circular economy-oriented dynamic capabilities for sustainable product design and end-of-life management: Insights from PLS-SEM and NCA

Drawing on the dynamic capabilities theory, a multi-method approach was used to examine the effects of circular economy-oriented dynamic capabilities on sustainable product design and end-of-life management. Partial Least Squares Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA) were employed on survey data from 285 manufacturing firms in Ghana. The findings show that whereas reconfiguring capabilities enhance sustainable end-of-life management, sensing and seizing capabilities were not direct predictors of sustainable end-of-life management. Nonetheless, sustainable product design was found to be a mechanism through which sensing and seizing capabilities promote sustainable end-of-life management. Also, apart from reconfiguring capabilities, sensing and seizing capabilities were positive predictors of sustainable product design. The NCA results suggest that all three circular economy-oriented dynamic capabilities (i.e., sensing, seizing, and reconfiguring capabilities) are must-have (necessary) conditions for sustainable product design and end-of-life management. We provide empirical evidence (via PLS-SEM and NCA) of the nice-to-have and must-have circular economy-oriented dynamic capabilities for sustainable product design and end-of-life management, besides highlighting sustainable product design as a mechanism through which these capabilities enhance sustainable product design.

A students’ behaviors in information security: Extension of Protection Motivation Theory (PMT)

ABSTRACT This study investigates information security behaviors among university students, focusing on the interplay of psychological and social factors influencing their behavioral intentions and actions. By integrating the Theory of Planned Behavior, Protection Motivation Theory, and General Deterrence Theory, the research offers a comprehensive understanding of factors such as self-efficacy, perceived risk vulnerability, response cost, and response efficacy. Utilizing structural equation modeling (SEM) and Necessary Condition Analysis (NCA), the study assesses the impact of these factors on students’ information security practices. Measurement items were developed based on recent empirical studies, ensuring relevance to the contemporary digital environment. The findings reveal significant associations between these factors and students’ security behaviors, providing insights into effective strategies for promoting information security awareness and practices. This research contributes to the academic discourse on digital security behaviors and offers practical implications for enhancing information security measures within university settings.

Dynamic spatial price equilibrium, dynamic user equilibrium, and freight transportation in continuous time: A differential variational inequality perspective

In this paper we provide a statement of dynamic spatial price equilibrium (DSPE) in continuous time as a basis for modeling freight flows in a network economy. The model presented describes a spatial price equilibrium due to its reliance on the notion that freight movements occur in response to differences between the local and distant prices of goods for which there is excess demand; moreover, local and distant delivered prices are equated at equilibrium. We propose and analyze a differential variational inequality (DVI) associated with dynamic spatial price equilibrium to study the Nash-like aggregate game at the heart of DSPE using the calculus of variations and optimal control theory. Our formulation explicitly considers inventory and the time lag between shipping and demand fulfillment. We stress that such a time lag cannot be readily accommodated in a discrete-time formulation. We provide an in-depth analysis of the DVI's necessary conditions that reveals the dynamic user equilibrium nature of freight flows obtained from the DVI, alongside the role played by freight transport in maintaining equilibrium commodity prices and the delivered-price-equals-local-price property of spatial price equilibrium. By intent, our contribution is wholly theoretical in nature, focusing on a mathematical statement of the defining equations and inequalities for dynamic spatial price equilibrium (DSPE), while also showing there is an associated differential variational inequality (DVI), any solution of which is a DSPE. The model of spatial price equilibrium we present integrates the theory of spatial price equilibrium in a dynamic setting with the path delay operator notion used in the theory of dynamic user equilibrium. It should be noted that the path delay operator used herein is based on LWR theory and fully vetted in the published dynamic user equilibrium literature. This integration is new and constitutes a significant addition to the spatial price equilibrium and freight network equilibrium modeling literatures. Among other things, it points the way for researchers interested in dynamic traffic assignment to become involved in dynamic freight modeling using the technical knowledge they already possess. In particular, it suggests that algorithms developed for dynamic user equilibrium may be adapted to the study of urban freight modelled as a dynamic spatial price equilibrium. As such, our work provides direction for future DSPE algorithmic research and application. However, no computational experiments are reported herein; instead, the computing of dynamic spatial price equilibria is the subject of a separate manuscript.

Role of online health communities in patient compliance: a social support perspective

Purpose Online health communities (OHC) can transform the healthcare industry, particularly in developing economies. Technology advancement and increased health literacy pave the way for these communities to become powerful tools for empowering patients. The purpose of this study was to empirically validate the linkages between social support and how it overarchingly influences patient compliance. Following social support theory, this study delineates how support from the community affects the patient–physician relationship (PERP) and consequently patient compliance regarding the treatment plan. This study also invents the role of patient trust in an OHC in moderating the relationship between PERP and engagement. Design/methodology/approach This paper is based on social support and empowerment theories to investigate the importance of social support in improving patients’ health behaviours and health outcomes via patient empowerment, patient engagement and patient compliance. The authors surveyed users from three Facebook cancer communities in India to collect data. The authors used partial least squares structured equation modelling and necessary condition analysis (NCA) with 265 participants to support the proposed model. Findings The result demonstrates that PERP is a crucial factor for patient engagement in OHC, and patient engagement has a significant effect on patient compliance. The results also showed that trust was a significant moderator between PERP and engagement. The NCA analysis shows all the relationships are significant; however, emotional support is not a necessary condition for PERP. Research limitations/implications By empowering cancer patients and enabling them to meet their emotional and informational needs through OHCs, the study model can aid in the development of solutions that will improve compliance with their treatment in an emerging economic context. The findings indicate the potential chain reaction of social support and PERP in online cancer health communities. This study also contributes to quantifying the social impacts of online healthcare services and how to enhance the healthcare compliance framework. Originality/value This study combines social support and empowerment theory with patient, physician, and technology to provide a fine-grained picture of PERP in OHC. It explains how social support in OHC promotes self-care behaviour. This linkage validation enables readers and the community at large to gain a more nuanced understanding of how social support – through PERP, engagement and trust – enables patient compliance using primary data.

Enhancing the energy level of regional digital innovation ecosystems: A configuration perspective.

This study introduces the concept of "energy level" into the analysis of innovation ecosystems. Drawing on the theory of "architects", we have identified the key architects of regional digital innovation ecosystems. By integrating Necessary Condition Analysis (NCA) and Fuzzy-set Qualitative Comparative Analysis (fsQCA), we examined the configuration effects of internal architects, external architects, and digital innovation habitats on the energy level of these ecosystems, utilizing data from 30 provinces in China as case studies. The results indicate that the contribution of a single architect to achieving a high energy level in a regional digital innovation ecosystem is limited and cannot be regarded as a necessary condition for driving a high energy level. However, core innovation actors and digital infrastructures emerge as more significant core conditions. The architects of regional digital innovation ecosystems exhibit multiple concurrent causal relationships. The configuration paths of high and non-high energy levels of ecosystems display a causally asymmetric "multiple paths to the same outcome" relationship. The three identified paths for driving high energy levels are categorized as "core actor-infrastructure"-driven paths. The findings of this paper hold substantial theoretical and practical significance for fostering the healthy development of regional digital innovation ecosystems.

Modelling Behavioural Factors Affecting Consumers’ Intention to Adopt Electric Aircraft: A Multi-Method Investigation

Electric aircraft are seen as a key option for reducing the environmental footprint of the aviation industry. This research aims to identify the factors that influence Turkish air travellers’ intentions to adopt electric aircraft by building upon the theory of planned behaviour (TPB). A structured online survey was developed to gather cross-sectional data from 217 air travellers using convenience sampling. The data were analysed through a multi-method approach, including structural equation modelling (SEM) for sufficiency analysis and necessary condition analysis (NCA) for necessity analysis. The findings reveal that attitudes, subjective norms, perceived behavioural control, personal moral norms, and green trust positively correlate with the intention to adopt electric aircraft, whereas perceived risk has a negative correlation. Moreover, the NCA indicates that attitudes, subjective norms, perceived behavioural control, personal moral norms, environmental knowledge, and green trust are necessary conditions for the intention to adopt electric aircraft, reinforcing these results. This study is the first empirical attempt to investigate the formation of the intention to adopt electric aircraft, built on both sufficiency and necessity logics.

Using necessary condition analysis to complement multigroup analysis in partial least squares structural equation modeling

With the growing importance of partial least squares structural equation modeling (PLS-SEM) in marketing and consumer research, the use of Multigroup Analysis (MGA) for discovering observed heterogeneity (i.e., differences in relationships between variables for subgroups of the population under investigation) and deriving relevant operational results has become of great interest. However, these analyses are based exclusively on an additive sufficiency logic and do not permit researchers to test and validate hypotheses drawing on a necessity logic, the latter having been the focus of recent significant developments. Addressing this concern, the present paper offers guidelines for combining the use of Necessary Condition Analysis (NCA) and MGA performed with PLS-SEM. Taken together, these analyses can explore and improve knowledge about predefined subgroups of interest, enhance the understanding of relationships, refine the role of specific key antecedents by discovering meaningful necessary conditions, and therewith, contribute to theorizing. An empirical illustration drawing on the relationship between corporate social responsibility and customer loyalty is developed in a step-by-step fashion to provide marketing researchers with the guidelines to conduct the MGA and NCA, and finally report and interpret the results in accordance with both the sufficiency and the necessity logics. This integrative procedure contributes to the advancement of PLS-SEM applications. By delivering a better understanding of the group-specific results of a PLS-SEM–based MGA in a necessity logic, it promotes the complementary usage of sufficiency and necessity logics and therefore helps researchers to uncover novel theoretical and practical results when evaluating the data.

Identifying precondition configurations of mathematics anxiety among middle school students in China: using NCA and QCA approaches.

Addressing mathematics anxiety is important to ensure that students achieve good academic performance and maintain their mental health during the critical middle school period. However, previous studies have focused on the separate effects of the preconditions for mathematics anxiety, ignoring the interaction of factors. Therefore, this study aims to identify the determinants of mathematics anxiety from the perspective of complex systems via necessary condition analysis (NCA) and qualitative comparative analysis (QCA). To the best of our knowledge, this is the first study to identify configurations of preconditions of mathematics anxiety among middle school students. A total of 183 middle school students aged 16 to 19 years (M age = 17.47, SD = 0.89) in China participated in this cross-sectional study. The outcome variable of the study is mathematics anxiety, and the condition variables include mathematics grade, parental support, learning motivation, learning planning, and learning interest. The necessity condition analysis shows that not all the condition variables constitute the necessity condition of mathematics anxiety alone. Four paths for the influence of multiple condition variables on mathematics anxiety are identified via the configuration analysis. Notably, even students with high mathematics scores and learning interest still experience mathematics anxiety due to a lack of practical parental support and learning motivation. High levels of parental support can exacerbate the mathematics anxiety of students under two conditions: 1) a lack of learning motivation and learning plans, and 2) interest in learning but low mathematics scores and unclear learning plans. This study highlights the need to consider the comprehensive impact of mathematics anxiety, and the findings will help educators and researchers identify the different characteristics of mathematics anxiety in student populations.

Impact of AI on Customer Experience in Video Streaming Services: A Focus on Personalization and Trust

In the digital entertainment landscape, AI-enhanced video streaming services like Netflix and Hulu significantly shape user experiences through AI-based recommendations. This study examines customer perceptions of these AI-driven suggestions, focusing on factors such as Perceived Interactivity, Service Quality, Commitment, Trust, and Personalization. Using data from a diverse sample in Klang Valley, Malaysia, the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). PLS-SEM models complex relationships to predict customer satisfaction, while NCA identifies essential conditions for desired outcomes in customer experience. Findings reveal that Personalization significantly influences satisfaction (path coefficient = 0.34), with Trust enhancing the impact of Perceived Interactivity (mediation effect size = 0.15). Expectancy confirmation also moderates the relationship between service attributes and satisfaction (β = 0.09). The results highlight the importance of tailored personalization and robust trust mechanisms in AI systems, emphasizing strategies to improve viewer retention and overall satisfaction.

Data vulnerability and privacy risk among hotel guests who share personal data

This research explores the guests’ perception toward data vulnerability and its impact on the privacy risk, privacy concern, and the perceived benefits of sharing personal data with hotels, which is in response to rising concerns about the personal data collection for service facilitation in hotels. A proposed research framework that explains the antecedents and outcomes of hotel guests’ privacy risk and privacy concern that is related to personal data sharing was examined using the generalized structured component analysis with measurement errors incorporated (GSCAM), the necessary condition analysis (NCA), and a fuzzy-set qualitative comparative analysis (fsQCA). The results expand the antecedents → privacy concerns → outcomes (APCO) model by determining a set of salient variables, such as data access, data breach vulnerabilities, privacy risk, and concern in regards to determining hotel guests’ perceived benefits of sharing personal data. This study provides valuable insights into privacy dynamics, enabling hotel professionals to develop targeted marketing strategies prioritizing both data utilization and guest privacy. It also suggests enhancing data security measures to mitigate concerns and foster trust among guests.

How can regional innovation ecosystems attain and maintain stable operation? - an investigation utilising NCA and fsQCA

ABSTRACT This study uses the Multi-Level Perspective (MLP) on socio-technical transitions to develop a theoretical model for analyzing the stable operation of regional innovation ecosystems. Focusing on 30 provinces in China, it employs Necessary Condition Analysis (NCA) and Fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine the configuration paths driving their stability. First, the findings reveal that innovation actors, resources, driving policies, industrial regulations, infrastructures, and the innovation environment are not individually necessary for stability. However, infrastructure is identified as a critical core condition. The study highlights a complex causal relationship and synergistic interplay among the six antecedent conditions. Second, the research identifies two paths to highly stable operation in regional innovation ecosystems: the ‘Innovation Actor + Infrastructure’ path and the ‘Infrastructure’ path. Finally, the results show that configurations for highly and non-highly stable operations exhibit causal asymmetry, indicating ‘different paths to the same destination.’ This study deepens theoretical insights into regional innovation ecosystems and offers actionable strategies for their stable operation.

Millennials' Insurance Product Purchase Intention in Malaysia: An Exploratory Study

This cross-sectional study was conducted to identify the factors influencing Malaysian millennials' purchasing intentions for an insurance product after post-COVID. This study applied the Stimulus-Organism-Response (SOR) model. In particular, it investigates the antecedents of perceived value, income protection, and financial security that led to Malaysian millennials' purchase intention of insurance products, to which similar studies received less attention. Judgmental sampling approaches were used to acquire the samples. The data was analysed using the Partial Least Square Structural Equation Modelling technique (PLS-SEM) followed by Necessary Condition Analysis (NCA). According to the PLS-SEM estimation, all hypotheses were statistically significant. The finding shows that income protection is the most critical factor influencing insurance product purchase intentions, followed by financial stability and perceived value. Meanwhile, NCA results also demonstrated that income protection is the most crucial must-have factor driving insurance product purchasing intentions. Perceived value has a greater impact than financial security and ranks as the second must-have factor contributing to purchase intention, followed by financial security. Lastly, NCA results suggest that tax savings are not a must-have factor in determining the perceived value of an insurance product. This study provides valuable insights and practical implications for industry and practitioners. Meanwhile, to fill a methodological gap, this study used PLS-SEM combined with the NCA to uncover the must-have factors contributing to Malaysian millennials' intention to purchase insurance products.

Exploring the missing link between top management teams' characteristics and environmental information disclosures of construction corporations

PurposeGiven the heavy pollution feature of the construction industry, construction corporations need to adopt an effective environmental governance strategy. The quality and quantity of environmental information disclosure (EID) implementation, as an essential part of a corporate environmental governance strategy, is impacted by the characteristics of the top management team (TMT). This paper aims to analyze the relationship between the demographic characteristics of the TMT (i.e. gender, age, tenure, educational level, and duality) and corporate EID.Design/methodology/approachUsing data from listed construction corporations generated between 2014 to 2018 in China, this study employs the Tobit regression model to test the research hypotheses. Also, this study applies a novel analytical approach, necessary condition analysis (NCA), to conduct a series of additional tests.FindingsThe results reveal that tenure and educational level are significantly and positively related to EID, while gender, age, and duality in the executive role are not significantly related to EID. When considering the TMT size as a moderator, the TMT age is positively related to the corporate EID, and the size of the TMT acts as a moderator to weaken the positive effect of the TMT age on the EID. The NCA results show that TMT gender, age, tenure, and educational level are necessary when the levels of EID exceed 40%.Originality/valueOur findings suggest that TMT characteristics have a relatively significant effect on corporate EID levels, which extends EID research to the construction industry. Corporate planners can endeavor to shape TMT characteristics to improve EID levels. The results of NCA provide insights into what TMT characteristics construction corporations need to satisfy in their pursuit of transparent EID, as well as the levels at which these characteristics are desired.

Pathways to e-participation diffusion: A societal and governance perspective

E-participation diffusion is influenced by the interactions of multiple contextual factors. This study examines how societal dynamics and governance (i.e., national culture, economic prosperity, human capital, population size, online trust, and regulation) interact to produce high and low levels of e-participation diffusion. The study uses fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) on a dataset of 88 countries collected from multiple sources. FsQCA reveals three paths for high e-participation diffusion (each includes either high online trust or high regulation combined with at least one additional condition) and a single path combining low online trust and regulation for low e-participation diffusion. NCA identifies that regulation, online trust, human capital, and economic prosperity are necessary conditions for high e-participation diffusion, while no necessary condition is identified for low e-participation diffusion. Uncovering casual mechanisms leading to high and low e-participation diffusion, the study contributes to the conversation on technology-mediated participatory governance interactions and guides decision makers in formulating targeted strategies to promote e-participation diffusion.

Natural resources, digital financial inclusion, and good governance nexus with sustainable development: Fuzzy optimization to econometric modeling

AbstractThis study aims to investigate the complex interplay between natural resources, digital financial inclusion, good governance, and sustainable development outcomes, employing a hybrid methodological approach which combines fuzzy‐set qualitative comparative analysis (fsQCA), necessary condition analysis (NCA), and econometric modeling. Drawing on data from 18 countries spanning 2013–2019, the study unravels the impact of these factors on sustainable development (SD) and explores the moderating role of governance. The findings reveal positive effects of digital financial inclusion, natural resources, and good governance on SD, with governance quality enhancing the relationship between digital financial inclusion and development outcomes. However, governance does not significantly moderate the link between natural resources and sustainability, which illustrates the need for tailored governance approaches in resource‐dependent contexts. Theoretical implications highlight the relevance of institutional theory in understanding the dynamic nature of development processes, while practical implications offer actionable insights to foster holistic and resilient pathways to sustainable development. Thus, the study contributes to advancing our understanding of the intricate relationships shaping SD outcomes and informs evidence‐based policy interventions in this critical domain.

How Business–Government Relationships Drive Digital Innovation and Entrepreneurship: A Study of 292 Cities in China Using NCA and TDQCA

Innovation is the driving force for achieving sustainable economic development, and healthy business–government relationships are the foundation and guarantee for promoting the sustainability of digital innovation and entrepreneurship. However, current academic research on the impact of business–government relations on digital innovation and entrepreneurship often neglects the configurational effects of various factors. Therefore, this study constructed an analytical framework from the new dimension of “close” and “clean” business–government relationships, selected 292 Chinese cities as research subjects, and employed the Necessary Condition Analysis (NCA) and Time-Differencing Qualitative Comparative Analysis (TDQCA) methods. From a configurational perspective, it explored the relationship between business–government relations and digital innovation and entrepreneurship. The results showed the following: Firstly, the various business–government relationship factors did not have a single linear impact on digital innovation and entrepreneurship, and configuration was more crucial than a single factor. Secondly, based on the integration of research findings and the theoretical framework, five successful configurations were proposed. However, these configurations possess certain adaptability and need to be tailored to local conditions. Thirdly, analyzing the three “non” condition variables in these five configurations, including “clean” business–government relationships, government efficiency, and new infrastructure, also contributed to enhancing the sustainability of digital innovation and entrepreneurship outcomes. Additionally, the study analyzed the implications of these critical configurations for five key stakeholders: government, enterprises, research institutions and academia, policymakers, and the public. Specifically, the government can implement policies tailored to local conditions to promote the sustainable development of digital innovation and entrepreneurship. These policies include increasing investment in digital infrastructure, simplifying approval processes, and enhancing the efficiency of government services.

The hustle behind knowledge: role of workplace ostracism and knowledge hiding towards quiet quitting in knowledge-intensive organisations

Purpose Given the workplace’s reinvention to accommodate the global pandemic’s novel conditions, knowledge hiding (KH) behaviour in knowledge-intensive organisations must be examined from a fresh perspective. In this context, the relationship between workplace ostracism (WO) as KH’s antecedent and quiet quitting (QQ) as its consequence is undertaken via the mediating role of KH behaviour among knowledge workers (KWs). Design/methodology/approach Through stratified sampling, data from 649 KWs is obtained to test the model. Partial least squares structural equation modelling (PLS-SEM) using SMART-PLS 4.0. software establishes a significant influence of WO on KH and QQ. KH significantly mediates the relationship between WO and QQ, highlighting its critical intermediary role PLSPredict evaluates the model’s predictiveness. WO and KH’s effects on QQ are examined using necessity logic by collectively applying PLS-SEM and necessary condition analysis (NCA). Findings The model wherein WO plays a significant role in increasing KH and QQ, with KH as a partial mediator in the relationship, has high predictive relevance. Moreover, NCA confirms WO as the key predictor variable that provides variance in QQ, followed by KH. The Importance-performance map analysis technique supports the study’s managerial implications. Originality/value This study enriches QQ’s emerging literature by empirically identifying its antecedents-WO and KH. Methodologically, this paper gives a model for using PLS-SEM and NCA together in relation to QQ by identifying WO as its necessary condition. Evidence of selected constructs’ interrelationships may help organisations draft leadership programmes to curtail KH and QQ behaviour.

‘Are you still watching?’ – A study on the predictors of the problematic practice of binge-watching

By implementing innovative ways of accessing the media, video-on-demand services have renewed the concept of watching television, leading to the growth and popularity of social behavior of content consumption in the form of marathons, known as binge-watching. There is an increase in literature discussions about potential adverse outcomes that can arise from the excess of these marathons. It is because the adversities of its excessive use can affect its users in the social, physical, and mental spheres. Given the relevance of this social problem, this research aims to understand the main determining predictors of the problematic practice of binge-watching. The research sample consisted of binge-watching practitioners (n=467). The linear and multivariate methods used Structural Equation Modeling by Partial Least Squares (SEM-PLS) and Necessary Condition Analysis (NCA). As a result, the study showed that the practice, associated with the psychological predisposition of individuals, can lead to the development of negative symptoms similar to addiction to various technologies, compromising the individual’s life both physically and psychologically. This phenomenon intensified during the COVID-19 pandemic when binge-watching was used for distractions, entertainment, and the management of negative sensations arising from the pandemic. Finally, this research contributes to the proposition of an original theoretical model on the problematic practice of binge-watching. It brings elements to reflect from the ESG point of view, as companies must commit to their social governance, thinking of strategies to optimize the obtaining profits, in the present study, subscriptions, without compromising the health of individuals.

Understanding Gen Z shoppers' interaction with customer-service robots: a cognitive-affective-normative perspective

PurposeLarge supermarket chains are adopting customer-service robots to improve service delivery in physical stores. Successful deployment of these robots depends on shoppers' willingness to interact with them, requiring an understanding of influencing factors. This study, grounded in the Cognitive-Affective-Normative (CAN) theory, seeks to systematically explore the factors influencing Gen Z shoppers' willingness to interact with customer-service robots.Design/methodology/approachA hybrid approach combining Structural Equation Modeling (SEM) and Necessary Condition Analysis (NCA) was employed to analyze survey data collected from 945 Gen Zs in the Czech Republic.FindingsThe results from SEM highlight significant cognitive, normative, and affective factors that influence the intention of Gen Z shoppers to interact with a customer-service robot. Specifically, cognitive factors such as effort and performance expectancy, along with normative factors like subjective norms, emerged as critical determinants. Furthermore, affective factors such as technology anxiety and positive emotions significantly influence users' readiness to use customer-service robots for service requests. The study also underscores that positive emotions, effort expectancy, performance expectancy, and subjective norms are vital prerequisites for interacting with customer-service robots.Originality/valueThe originality of this work lies in its two significant contributions to the burgeoning field of SRs in retail literature. First, it extends the CAN theory to the context of SRs among Gen Z shoppers in Czechia, thereby enriching the existing literature on SRs in retail. Second, by employing a hybrid analytical approach, our research offers both empirical and methodological advancements, providing rigorous insights crucial for enhancing the understanding of the pivotal factors influencing shoppers' interactions with SRs in physical store environments.

Insignificant but Essential: The Critical Role of Non-Significant Variables through Necessity Logic in Sport Event Tourism Context

This study explores the application of Single Necessary Condition Analysis (NCA) alongside traditional regression-based techniques, such as Structural Equation Modeling (SEM), to provide a comprehensive understanding of consumer behavior in sport and tourism settings. Traditional methods, including SEM, often rely on additive logic, which predicts outcomes using multiple variables that can compensate for each other. While useful, this approach may offer an incomplete picture of complex consumer phenomena. In contrast, necessity logic, exemplified by NCA, identifies conditions that must be present for an outcome to occur. This study applies NCA to evaluate the essential factors influencing intentions to visit sport events in Bangkok, Thailand, specifically focusing on attitudes, subjective norms, and perceived behavioral control as necessary conditions. The findings indicate that if these conditions are not met, the intention to visit a sport event typically will not occur. By integrating both necessity and additive logics, this study reveals that all variables in the Theory of Planned Behavior (TPB) are indispensable for forming an intention to visit a sport event. The analysis shows that attitudes, subjective norms, and perceived behavioral control are necessary conditions, even though subjective norms and perceived behavioral control may not appear significant in traditional SEM tests. The study underscores the importance of considering multiple causal perspectives—deterministic, probabilistic, and typicality—to achieve a holistic understanding of consumer intentions. This dual approach ensures that significant variables are not overlooked, providing robust support for the TPB in the context of sport event marketing. Future research should continue to incorporate complementary perspectives to enhance the accuracy and depth of consumer behavior analysis in various settings.