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Necessary conditions represent the factors that cannot be compensated but must be present to aim the desired outcome; if a necessary condition is absent, the outcome will not exist. This logic of necessity causality differs from the conventional logic that has been evaluated by the methods drawing the lines “through the middle of the data” (e.g., regression and SEM). The authors argue that the empirical investigation of necessity causality has been largely ignored in hospitality and tourism literature although the notion of necessary causes for achieving certain outcomes is widespread throughout the studies. Thus, the authors introduce “necessary condition analysis” (NCA) as a suitable analytical method to identify necessary conditions in hospitality and tourism research. This chapter provides details on the underlying logic, key advantages, and an illustrative example of NCA. The chapter concludes by offering a few recommendations for future NCA applications in hospitality and tourism research.

The purpose of this paper is to show that necessary condition hypotheses are important in operations management (OM), and to present a consistent methodology for building and testing them. Necessary condition hypotheses (“X is necessary for Y”) express conditions that must be present in order to have a desired outcome (e.g. “success”), and to prevent guaranteed failure. These hypotheses differ fundamentally from the common co‐variational hypotheses (“more X results in more Y”) and require another methodology for building and testing them.

The paper reviews OM literature for versions of necessary condition hypotheses and combines previous theoretical and methodological work into a comprehensive and consistent methodology for building and testing such hypotheses.

Necessary condition statements are common in OM, but current formulations are not precise, and methods used for building and testing them are not always adequate. The paper outlines the methodology of necessary condition analysis consisting of two stepwise methodological approaches, one for building and one for testing necessary conditions.

Because necessary condition statements are common in OM, using methodologies that can build and test such hypotheses contributes to the advancement of OM research and theory.

The purpose of this paper is to examine the claim that the application of human factors (HF) knowledge can improve both human well‐being and operations system (OS) performance.

A systematic review was conducted using a general and two specialist databases to identify empirical studies addressing both human and OS effects in examining manufacturing OS design aspects.

A total of 45 empirical studies were found, addressing both the human and system effects of OS (re)design. Of those studies providing clear directional effects, 95 percent showed a convergence between human effects and system effects (+, + or −,−), 5 percent showed a divergence of human and system effects (+,− or −,+). System effects included quality, productivity, implementation performance of new technologies, and also more “intangible” effects in terms of improved communication and co‐operation. Human effects included employee health, attitudes, physical workload, and “quality of working life”.

Future research should attend to both human and system outcomes in trying to determine optimal configurations for OSs as this appears to be a complex relationship with potential long‐term impact on operational performance.

The application of HF in OS design can support improvement in both employee well‐being and system performance in a number of manufacturing domains.

The paper outlines and documents a research and practice gap between the fields of HF and operations management research that has not been previously discussed in the management literature. This gap may be inhibiting the design of OSs with superior long‐term performance.

In organizational research the object of study is often a process, that is, a complex of events and activities that unfolds over time. In this chapter we focus on temporally ordered configurations, which can be defined as those configurations in which conditions occur in a specific temporal order. We illustrate the aims, characteristics, and limitations of several approaches that have been proposed as tools for the analysis of temporal order. Our illustration involves an analysis of the “gestation activities” of nascent entrepreneurs, that is, persons involved in the creation of a new firm. We aim to identify temporal sequences of gestation activities that generate or allow a successful outcome of the gestation process, while an occurrence of the same activities in another temporal order will not generate or allow that outcome. First we discuss Event Structure Analysis and Optimal Matching and conclude that these approaches cannot provide the kind of analysis that we are aiming at in this chapter. Then we discuss Temporal Qualitative Comparative Analysis, for which our analysis points to technical limitations that constrain its application. We then present and discuss an alternative approach, Temporal Necessary Condition Analysis.

This study investigates the influence of consumption values on green Fast-Moving Consumer Goods (FMCG) purchase behaviour in the context of green household cleaning products in the Western Province of Sri Lanka.

We used the survey strategy and 326 effective responses as the sample of this study.

Our findings reveal that specific consumption values, specifically functional, conditional and epistemic values, significantly impact green FMCG purchase behavior towards green household cleaning products. However, social and emotional values did not substantially influence this behavior.

The results of our study suggest practical implications for green FMCG marketers aiming to boost consumer adoption of green household cleaning products in Sri Lanka. To achieve this, marketers should focus on enhancing consumer value perceptions and strategically emphasize the consumption values consumers prioritize. Green FMCG marketers have a competitive advantage in the Sri Lankan market by doing so.

This research addresses a notable gap in the literature concerning green FMCG purchase behavior related to green household cleaning products within international and local contexts. Furthermore, this study distinguishes itself by adopting the Theory of Consumption Values as its foundational theory, offering fresh insights compared to previous research employing alternate theories, such as the Theory of Planned Behavior and the Theory of Reasoned Action, to examine similar phenomena.

The COVID-19 pandemic has generated unprecedented public fear, impeding both individuals’ social life and the travel industry as a whole. China was one of the first major countries to experience the COVID-19 outbreaks and recovery from the pandemic. The demand for outings is increasing in the post-COVID-19 world, leading to the recovery of the ride-sharing industry. Integrating protection motivation theory and the theory of reasoned action, this study aims to investigate ride-sharing customers’ self-protection motivation to provide anti-pandemic measures and promote the resilience of ride-sharing industry.

This study followed a two-phase mixed-methods design. In the first phase, the authors executed a qualitative study with 30 interviews. In the second phase, the authors used the results of the interviews to inform the design of a survey, with which 272 responses were collected. Both studies were conducted in China.

The present results indicate that customers’ perceived vulnerability of COVID-19 and perceived COVID protection efficacy (self-efficacy and response efficacy) are positively correlated with their attitude toward self-protection, thus leading to their self-protection motivation during the rides. Moreover, subjective norms and customers’ distrust appear to also impact their self-protection motivation during the ride-sharing service.

The present research provides one of the first in-depth studies, to the best of the authors’ knowledge, on customers’ protection motivation in ride-sharing services in the new normal. The empirical evidence provides important insights for ride-sharing service providers and managers in the post-pandemic world and promote the resilience of ride-sharing industry.