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This study examines the impact of outcome uncertainty on the National Football League (NFL) secondary ticket market prices. As a demand-driven market, it is essential to comprehend how resellers respond to outcome uncertainty, one of the consumer demand factors in sports.

Using real-time ticket prices and money lines as a proxy of the probabilities of winning, this study employs a regression analysis and examines 33,554 price observations from the NFL’s secondary ticket market partner, StubHub.

The result shows a positive relationship between outcome uncertainty and secondary market ticket prices, indicating that resellers adjust the prices in response to the level of outcome uncertainty and put more value on games with greater uncertainty. This finding confirms the demand-driven nature of the secondary ticket market, as outcome uncertainty is one of the demand factors in sports.

This study links the uncertainty of outcome hypothesis with secondary ticket market pricing and fills a gap in the literature by providing an important perspective on games with uncertainty in the secondary ticket market. Outcome uncertainty has limited understanding in relation to secondary ticket market pricing despite its relationship with consumer demand. The positive relationship between outcome uncertainty and the ticket prices, grounded in real-time price data and win probability from sport betting markets, enhances our understanding of price determinations in the secondary ticket market.

People usually try to avoid uncertainty. Recently, however, uncertainty has become an emerging marketing tool in the hedonic product industry. In the case of blind box consumption, for example, the consumers become addicted to the uncertainty created by businesses, leading to repeat purchases and even indulgences. Previous research has, yet, to focus on the impact of uncertainty on indulgence and the role of emotions.

This paper constructs and validates a chain mediation model of uncertainty triggering indulgent consumption based on the information gap theory, positive emotion theory and uncertainty resolution theory and examines the difference between resolved and unresolved uncertainty. This study also explores differences in the impact of whether uncertainty is resolved on emotions. The uncertainty-resolved group elicited a more positive emotional response than the uncertainty-unresolved group, leading to a more indulgent consumption.

The results of three studies show that uncertainty influences indulgent consumption through curiosity and positive emotion, and that curiosity and positive emotion play separate and chain mediating roles between uncertainty and indulgent consumption, respectively. We validate our central hypothesis with questionnaires among blind box consumer groups, examining the moderating role of perceived luck and risk preferences.

The findings shed new light on firms' use of uncertainty to promote consumer purchases.

This chapter explores the strategic responsiveness of commodity multinationals operating in developing countries to the uncertainties raised by the emergent European Union (EU) sustainability regulation. The study applies deductive theory triangulation to derive five response propositions, subsequently contrasted with inductive insights from an exploratory single-case study. The research involves in-depth interviews with a mix of senior and middle management and numerous external stakeholders. Empirical findings are discussed through storytelling and retrospective sensemaking and cross-checked against corporate documents, archive material, and online articles for added validation. This chapter concludes that an authentic commitment to corporate social responsibility and creating shared value can enhance the multinational enterprise (MNE)’s resilience and responsiveness to regulatory uncertainty, especially when combined with early signal scanning and real options reasoning. Through varied, first-hand insights, the case study demonstrates the role of reputation, core values, and ethical leadership in support of effective stakeholder engagement capabilities and the MNE’s ability to develop viable collaborative solutions to uncertainties implied by evolving sustainability regulation and stakeholder expectations. Taking an evolutionary view, this chapter introduces a process perspective on sustainability transition, relevant to firms seeking a shift in focus from mere compliance toward strategic responsiveness founded on adaptability and renewal.

Export market orientation can be broadly divided into intelligence (generation and dissemination) and responsiveness activities. Although previous studies assess intelligence and responsiveness activities, little is known about what type of international channel partner acts as an enabling condition for the impact of these activities on export venture performance. This study aims to examine the extent to which the selection of international channel partners through word-of-mouth referrals versus direct contacts affects the benefits of intelligence and responsiveness activities.

Data were collected from 246 exporting manufacturers in Japan. To test the hypotheses, we conducted regression analyses using a subjective performance measure at the venture level. We also performed a post hoc analysis using objective performance measure at the function level.

We find that the extent to which international channel partners are selected through word-of-mouth referrals has a moderating role in the export market-oriented activities–performance linkages. Specifically, it acts as an enabling condition for intelligence activity and a disenabling condition for responsiveness activity.

This study contributes to a better understanding of export market orientation by classifying it into intelligence and responsiveness activities and providing empirical evidence on their different interaction effects with partner selection. It also contributes to the elaboration of agency theory by offering insights into the fit between task characteristics and contract type. Our study is critical for business managers as it suggests guidelines for manufacturing exporters engaging in export market-oriented behaviors and export channel management.

The construction industry is a major economic driver in Malaysia, playing a pivotal role in the developing nations economic growth. Malaysia's reliance on labor-driven construction practices often sees local industry lagging in adopting technological advancements common to the construction sector on a global scale. This study investigates the challenges faced by project players in using new construction industrial revolution (IR) 4.0 technologies and the difficulties in implementing these technologies in construction projects.

A quantitative survey was distributed to 183 practitioners in the Malaysian construction industry. The collected data (N = 121) has been analyzed using statistical software to calculate relative importance index values for the identified factors. A triangulation approach to validate the factors obtained from the survey was conducted with an expert group to ensure there were no additional considerations identified in the study.

The study results show that the main factors in adopting construction IR 4.0 technologies are 1) high implementation costs, 2) hesitation to adopt technologies, 3) lack of standards, 4) legal and contractual uncertainty and 5) complexity. By investigating these factors, cost and regulation issues can gradually be resolved, with construction firms implementing new technologies, educating workers and ensuring government involvement in training for skill development to support IR 4.0.

The outcome of these efforts to resolve construction productivity would be beneficial in their industry impact on practice and digital transformation. Additionally, the results add to the body of knowledge for construction practitioners and technology developers to work together efficiently on the implementation of construction 4.0 technologies.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This study investigates the economic outcomes of the strategic deviation (SD), the fundamental and crucial question in institutional theory and strategic management. Previous studies have yielded contradictory findings. This study reconciles conflicting results by distinguishing the effects of the SD on financial and market performance, examining the mechanism of financing constraints and the boundary condition of institutional investor heterogeneity.

This research collected data from Chinese A-shares listed manufacturing firms from 2009 to 2021 from the CSMAR and Wind databases. This study conducted empirical tests using OLS models with Stata 15.

Empirical results demonstrate that the SD has different impacts on different dimensions of performance. The SD negatively impacts financial performance while positively impacts market performance. Financing constraints mediate the main effects. Moreover, transactional institutional investors positively moderate the negative effect of the SD on financial performance, whereas stable institutional investors negatively moderate the positive effect of the SD on market performance.

By systematically revealing how the SD has different effects on financial and market performance, this study reconciles the debate on the SD between institutional theorists and strategy scholars. This research makes contributions to the research stream by providing reasonable explanations for conflicting conclusions. Furthermore, by introducing the overlooked perspective of financing constraints, this research identifies crucial mediating mechanisms and highlights the double-edged effect of financing constraints, enriching our understanding of financing constraints. Finally, this study investigates the moderating effects of institutional investor heterogeneity, thereby making valuable contributions to the comprehension of boundary conditions.

The purpose of this paper is to examine how individual risk preference influences the borrowing of payday loans – a prevalent type of cash loan in the USA with exorbitantly high-interest rates. Additionally, this paper tests how risk preference determines other alternative financial services (AFS), including pawn shops, rent-to-own purchases, title loans, etc.

The author applies Probit and Tobit regressions to test the relationship between individual risk preference and payday borrowing, based on the state-by-state survey data from National Financial Capability Study (NFCS) sponsored by Financial Industry Regulatory Authority (FINRA) Investor Education Foundation.

Individuals with higher risk tolerance are more likely to borrow payday loans and other AFS, after controlling for financial situation, financial literacy, overconfidence and demographic features.

This paper is the first to study risk preference as an explanation to the high cost and widely used payday loan services in the United States of America. This study provides evidence that these cash loans are determined by inherent human characteristics. The finding provides new insight for the policymakers and regulators in the consumer debt market.

The purpose of this paper is to investigate the factors that influence business students’ adoption of e-learning systems by merging innovation diffusion theory (IDT) and the teaching for professional competence model (TPCM).

Snowball sampling was used to conduct the survey. In addition, 217 responses were obtained from students at private educational institutions. Similarly, literature on the determinants of e-learning adoption, TPCM, and IDT were reviewed to contribute to the factors that are instrumental in determining e-learning systems adoption.

The findings of the study show that e-learning systems adoption is influenced by factors such as online collaborative learning (OCL) and technology self-efficacy. Above all, the OCL variable was found to be influential in determining students’ adoption of e-learning systems platforms. On the contrary, perceived attributes such as perceived compatibility and perceived relative advantage were found not to be significant determinants of e-learning systems adoption.

This study contributed not only to the theoretical extensions but also to practical implications, which would benefit the policymakers of higher education providers in terms of e-learning system adoption in the country.

IDT and TPCM models are evaluated alongside additional variables, namely, OCL and technology self-efficacy. As a result, this paper will serve as a useful reference guide for academicians, higher education administrators, and future researchers.

In a dynamic, continuously evolving sports landscape, social media have become an indispensable tool for sports organizations to cultivate meaningful connections with fans. The rapid pace of technological advancements has elevated these digital platforms from a supplementary role to a pivotal position within strategic management frameworks. The existing literature explores how football clubs can utilize social media, but analyzing social media strategies within the context of football leagues is lacking. The absence of comparative studies benchmarking clubs across different geographical regions while simultaneously analyzing multiple social media platforms is especially noteworthy. In this study, a comprehensive analysis of social media engagement is undertaken within esteemed football leagues spanning Europe, South America and North America.

Drawing on relationship marketing and employing content analysis as a methodological tool, the study examined 10,772 posts from the official accounts of eight football leagues on Facebook, Twitter and Instagram.

Across the leagues, the findings reveal that content quality drives engagement more than frequency. In addition, several format combinations were identified that facilitate engagement and Instagram emerged as the top social media platform for generating fan engagement.

This is one of the first empirical studies focusing on optimizing the use of social media to amplify fan engagement across various geographies and social media accounts and formats simultaneously.