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The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

Drawing on the elaboration likelihood model (ELM), the authors examine the influence of perceived professor teaching qualities, as central cues, on online professor ratings. Also, our study investigates how the volume and period of reviews, as peripheral cues, affect online professor ratings.

Leveraging stratified random sampling, the authors collect reviews of 892 Information Systems professors from 250 American universities. The authors employ regression models while conducting robustness tests through multi-level logistic regression and causal inference methods.

Our results suggest that the central route from perceived professor qualities to online professor ratings is significant, including most qualitative pedagogical factors except positive assessment. In addition to course difficulty, the effect of the peripheral route is limited due to deficient diagnosticity.

Our primary concern about the data validity is a lack of a competing and complementary dataset. However, an institutional evaluation survey or an experimental study can corroborate our findings in future research.

Online professor review sites can enhance their perceived diagnosticity and credibility by increasing review vividness and promoting site interactivity. In addition to traditional institutional evaluations, professors can obtain insightful feedback from review sites to improve their teaching effectiveness.

To our best knowledge, this study is the first attempt to employ the ELM and accessibility-diagnosticity theory in explicating the information processing of online professor reviews. It also sheds light on various determinants and routes to persuasion, thus providing a novel theoretical perspective on online professor reviews.

In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.

This study aims to endeavor to shed light on the underlying causal mechanisms behind the failure of startups by examining the failure process in such organizations. To achieve this goal, the study conducted a comprehensive review of the literature on the definition of failure and its various dimensions, resulting in the compilation of a comprehensive list of causes of startup failure. Subsequently, the failure process was analyzed using a behavioral strategy approach that encompasses rationality, plasticity and shaping, as well as the growth approach of startups based on dialectic, teleology and evolution theories.

The proposed research methodology was a case study using process tracing, with the sample being a failed platform in the ride-hailing technology sector. The causal mechanism was further explicated through the combined application of the behavioral strategy approach and interpretive structural modeling analysis.

The findings of the study suggest that the failure of startups is a result of interlinked causes and effects, and growth in these organizations is driven by dialectic, teleology and evolution theories.

The outcomes of the research can assist startups in formulating an effective strategy to deliver the right value proposition to the market, thereby reducing the chances of failure.

Despite the increasing relevance of seamless shopping experience in an omnichannel context, research on how seamless shopping experience affects customers’ word of mouth on social media (sWOM) remains scant. Based on the attribution theory, this study aims to investigate the effects of seamless shopping experience types on customers’ sWOM intentions from the perspective of smart-shopping feelings and validated the moderation role of shopping orientation.

Using a data set of 301 omnichannel customers, three scenario-based experiments were conducted to address the research questions.

An efficient and interconnected experience is more likely to positively affect sWOM intentions than an inefficient but interconnected experience. Furthermore, smart-shopping feelings were found to have a significant mediating effect. For experiential-oriented shoppers, the positive relationship between an efficient and interconnected experience, smart-shopping feelings and sWOM intentions was significantly strengthened.

This research contributes to the sWOM and omnichannel service experience literature by investigating the influences of seamless shopping experience types on customers’ sWOM intentions. This research also provides recommendations for designing and delivering a superior, seamless shopping experience for omnichannel shoppers.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

Despite the wide research and discussion on international performance, innovation and digital resilience dimensions of enterprises, the investigation and understanding of their interrelations seem to be limited. The purpose of this study is to identify the influential factors affecting the mentioned dimensions, determine the causal relationships among these identified factors and finally evaluate their importance in an aggregated framework from the viewpoint of small and medium-sized enterprises (SMEs).

A hybrid methodology is used to achieve the objectives. First, the main factors of international performance, innovation and digital resilience are extracted by an in-depth review of the literature. These factors are then screened by expert opinions to localize them in accordance with the conditions of an emerging economy. Finally, the relationship and the importance of the factors are determined using an uncertain multi-criteria decision-making (MCDM) approach.

The findings reveal that there is a correlation between digital resilience and innovation, and both factors have an impact on the international performance of SMEs. The cause-or-effect nature of the factors belonging to each dimension is also determined. Among the effect factors, business model innovation (BMI), agility, product and organizational innovation are known as the most important factors. International knowledge, personal drivers and digital transformation are also determined to be the most important cause factors.

This study extends the literature both in methodological and practical directions. Practically, the study aggregates the factors in the mentioned dimensions and provides insights into their cause-and-effect interrelations. Methodologically, the study proposes an uncertain MCDM approach that has been rarely used in previous studies in this field.

Exploiting a novel measure of innovation, the authors investigate whether independent directors improve innovation efficiency. This novel measure of innovation captures the extent to which the firm generates revenue from its research & development and is, therefore, more economically meaningful. The authors also use a text-based measure of innovation.

The authors rely on a quasi-natural experiment based on the passage of the Sarbanes-Oxley Act of 2002 that compelled certain firms to raise board independence. The difference-in-difference analysis is far less vulnerable to endogeneity and is more likely to show a causal influence, rather than a mere association.

The results show that more independent directors improve innovation efficiency significantly. Specifically, firms forced to raise board independence experienced a much higher increase in innovation than those not required to change their board composition. The authors also explore another novel measure of innovation, a text-based metric of innovation.

The research is original in several ways. First, the authors take advantage of an exogenous regulatory shock as a quasi-natural experiment. This approach is far less susceptible to endogeneity. Second, the authors use a novel measure of innovation efficiency, i.e. research quotient, which is more economically meaningful. Finally, the authors use a unique measure of innovation derived from powerful textual analysis.

Risk factors related delay hinder the schedule performance of most construction projects in the world. It is a critical challenge to realize the advantages of prefabricated construction projects (PCPs) under the negative effect of schedule delay. This paper aims to propose an exhaustive list of risk factors impeding the progress of PCPs and evaluate the collected risk factors based on the cause–effect relations. The ultimate goal is to improve the understanding of the complex relations among various risk factors related delay in PCPs, and also offer managers a reference on aspect of schedule risk management.

This paper proposes a hybrid method of GT–DEMATEL–ISM, that is combing grounded theory, DEMATEL (decision-making trial and evaluation laboratory) and ISM (Interpretative Structural Modeling), to collect, evaluate and structure risk factors related delay for PCPs. The research procedure of this methodology is divided into three stages systematically involving qualitative and quantitative analysis. In the first stage, GT is utilized to implement qualitative analysis to collect the risk factors leading to schedule delay in PCPs. While, the quantitative analysis is to analyze and evaluate the collected risk factors based on the cause–effect relations in the next two stages evaluation by the DEMATEL focuses on quantifying the priority and intensity of the relations between factors. Additionally, ISM is employed to construct the hierarchical structure and graphically represent the pairwise relations between factors.

The outcome of qualitative investigation by grounded theory proposes a theoretical framework of risk factors related delay for PCPs. The framework contains three levels of category, namely, core category, main category and initial category and provides a list of risk factors related delay. Following this finding, evaluation results by the DEMATEL classify factors into cause and effect groups and determine 11 critical delay risk factors. Meanwhile, the findings show that risks referring to organizational management issue foremost impact the progress of PCPs. Furthermore, a systemic multilevel hierarchical structure model is visually constructed by ISM to present the pairwise linkages of critical factors. The model provides the risk transmission chains to map the spread path of delay impact in the system.

The contribution of the study involves twofold issues. Methodologically, this research proposes a hybrid method GT–DEMATEL–ISM used to identify and analyze factors for a complex system. It is also applicable to other fields facing similar problems that require collecting, evaluating and structuring certain elements as a whole in a comprehensive perspective. The theoretical contribution is to fill the relevant research gap of the existing body of knowledge. To the best knowledge of the authors, this paper is the first attempt to integrate qualitative and quantitative research for risk analysis related delay and take the insight into the whole process of PCPs covering off-site manufacture and on-site construction. Furthermore, the analysis of findings provided both a micro view focusing on individual risk factor and a managerial view from a systematic level. The findings also contribute the effective information to improve the risk management related schedule delay in PCPs.