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1 – 10 of 12Ismael Castillo-Ortiz, Minwoo Lee, Scott Taylor and Diego Bufquin
This paper aims to uncover patterns of Mexican craft beer consumers and guide companies’ decisions in the creation of new products, marketing strategies, advertising and promotion…
Abstract
Purpose
This paper aims to uncover patterns of Mexican craft beer consumers and guide companies’ decisions in the creation of new products, marketing strategies, advertising and promotion to increase craft beer sales and contribute to faster growth.
Design/methodology/approach
This is a conjoint analysis with a selection of attributes for new or renewed products, marginal disposition to pay for particular characteristics through brand-specific choice-based design, and market simulation.
Findings
This paper clearly demonstrates consumers’ preferences and willingness to pay in Mexico, with a cutting-edge market research technique combining the prioritization of preferred craft beer characteristics, and the price consumers are willing to pay for such product characteristics.
Research limitations/implications
The study's sample size of 501 responses is relatively small compared to the total number of craft beer consumers in Mexico. To enhance the validity and reliability of the findings, future studies should aim to obtain larger samples and compare their results with those of this study.
Practical implications
This study has important implications for craft beer producers, allowing them to develop targeted craft beers with appealing attributes for Mexican consumers, such as color, aroma intensity, alcohol degree intensity, bitterness, foam level and price.
Social implications
This study's market forecasting simulation technique is based on assumptions of consumer behavior and market dynamics. Although relevant variables were considered, unanticipated external factors or market changes could impact the forecasts' accuracy. This will allow for a more comprehensive understanding of craft beer consumer preferences in different markets and enhance the reliability of forecasting techniques.
Originality/value
This paper informs craft beer producers by providing valuable knowledge on customers’ preferences and willingness to pay to enhance craft beer companies’ product development processes.
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Stephen Wilkins, John J. Ireland, Joe Hazzam and Philip Megicks
To minimize customer churn, many service providers offer consumers the option of automatic contract renewal at the end of a contract period. Such agreements are known as rollover…
Abstract
Purpose
To minimize customer churn, many service providers offer consumers the option of automatic contract renewal at the end of a contract period. Such agreements are known as rollover service contracts (RSCs). This research quantifies the effect of RSCs and other related factors, such as incentives, on consumers' service choice decisions.
Design/methodology/approach
The study adopts choice-based conjoint analysis to assess the effect of RSCs on consumers' choices and to determine whether effect size varies when selecting a cell phone network or gym/leisure club provider, which represent lower-priced utilitarian and higher-priced hedonic services.
Findings
It was found that RSCs produce negative perceptions and intended behaviors for the majority of consumers across different product types. Nevertheless, as explained by social exchange theory, many individuals may be persuaded to enter into a RSC on the basis of reciprocity if they are offered an incentive such as a price discount or free product add-on.
Originality/value
In the marketing domain, this is the first comprehensive study to quantify the role of contract type among a range of other factors in consumers' decision-making when selecting a service. The authors' results offer context-specific implications for service marketers. First, RSCs are perceived more negatively in high-priced hedonistic categories, especially among those with lower incomes. Second, price discounts are more effective than product add-ons for motivating hedonic purchases, while product add-ons work better with utilitarian services.
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Michael Fuchs, Guillaume Bodet and Gregor Hovemann
While consumer preferences for sporting goods have been widely researched within sport management, literature is lacking on aspects of social and environmental sustainability…
Abstract
Purpose
While consumer preferences for sporting goods have been widely researched within sport management, literature is lacking on aspects of social and environmental sustainability. Accordingly, this study aims to investigate the role of social and environmental sustainability for purchase decisions of sportswear and compares them to the role of price and functionality.
Design/methodology/approach
Based on a conjoint analysis among 1,012 Europeans, the authors conducted a two-step cluster analysis. First, the authors investigated the number of segments via Ward’s method. Second, the authors ran a k-means analysis based on part-worth utilities from the conjoint analysis.
Findings
The authors identified four segments which differ in terms of preferred product attributes, willingness to pay, and sociodemographic, behavioral, and psychographic characteristics: undecided, sustainable, price-focused and function-oriented consumers. Based on this segmentation, the authors found that the importance of social and environmental sustainability is growing, but not among all consumers.
Research limitations/implications
The generalizability of the study is limited since it is not built on a sample representative for the included European countries, it focuses on a single product, and participants are potentially subject to a social desirability bias.
Originality/value
The consumer analysis comprises the uptake of attributes related to social and environmental sustainability. The authors thereby address a literature gap as previous research (thematizing sporting goods) in the sport management field has often neglected sustainability elements despite their rapidly growing importance within the sport sector.
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Hua Meng and Hannan Sadjady Naeeni
This study aims to explain why low social conduct in corporate social responsibility (SC-CSR), especially employee exploitation, has a stronger negative impact on consumer…
Abstract
Purpose
This study aims to explain why low social conduct in corporate social responsibility (SC-CSR), especially employee exploitation, has a stronger negative impact on consumer reactions for service firms than for manufacturing firms.
Design/methodology/approach
Five experiments compared consumer reactions to service and manufacturing firms with low SC-CSR. Study 1 used a choice-based conjoint design to examine the relative importance of various shared attributes when consumers chose services versus goods. Study 2 revealed that low SC-CSR led to more pronounced negative consumers reactions toward service firms. Studies 3A and 3B explained this difference through a serial mediation analysis. Study 4 ruled out an alternative explanation regarding the differentiated effects.
Findings
The results reveal that consumer reactions to employee exploitation in service firms are more negative compared to manufacturing firms. This is because consumers’ sense of presence (i.e. feeling of being there) is stronger in a service setting, leading to more intense empathetic emotions toward service employees.
Originality/value
This research contributes to the CSR literature by challenging the conventional notion that sweatshops are more problematic for manufacturing firms. By contrast, the results indicate a stronger negative effect on service firms. It contributes to the services marketing literature by conceptualizing a novel cognitive mechanism. Traditionally, consumers’ negative reactions are driven by anger. However, the authors show that empathetic feelings toward mistreated employees play a predominant role. While it is imperative for all firms to ensure fair treatment of their employees, the findings underscore the heightened significance of this aspect for service firms, given their susceptibility to more pronounced negative effects.
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V.T. Rakesh, Preetha Menon and Ramakrishnan Raman
Pricing is widely acknowledged as a market entry challenge for servitising companies. The purpose of this research is to ascertain the attributes that contribute to willingness to…
Abstract
Purpose
Pricing is widely acknowledged as a market entry challenge for servitising companies. The purpose of this research is to ascertain the attributes that contribute to willingness to pay (WTP) for industrial services and suggest incorporating those attributes to a pricing model.
Design/methodology/approach
Three attributes (Quality of Service, Nearness of Service Provider and Brand Equity of Service Provider) were analyzed at three respective levels to ascertain their importance on WTP. Conventional conjoint analysis (CCA), using an orthogonal design, was the method used. The 346 respondents were decision-makers and top management professionals from various industries.
Findings
Brand Equity emerged as the most significant attribute contributing to WTP, having more than 45% importance – followed by the Quality and Nearness.
Research limitations/implications
The scope of the study is limited to the industries and its Allies. However, the relative importance of the attributes may vary depending on the type of service.
Practical implications
The importance of attributes and their WTP preference helps future researchers create a pricing model involving these attributes. This helps service providers price their services rationally, thus succeeding in servitization.
Social implications
Product life is extended because the manufacturers themselves are servicing it and also help recycle the product with their expertise. Servitization is also helpful for the Indian economy, as it is turning into a manufacturing economy.
Originality/value
This research investigates three attributes that contribute to WTP, in accordance with their level of contribution. It also provides a direction to establish an adequate pricing model for industrial services.
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Khaled Hamad Almaiman, Lawrence Ang and Hume Winzar
The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.
Abstract
Purpose
The purpose of this paper is to study the effects of sports sponsorship on brand equity using two managerially related outcomes: price premium and market share.
Design/methodology/approach
This study uses a best–worst discrete choice experiment (BWDCE) and compares the outcome with that of the purchase intention scale, an established probabilistic measure of purchase intention. The total sample consists of 409 fans of three soccer teams sponsored by three different competing brands: Nike, Adidas and Puma.
Findings
With sports sponsorship, fans were willing to pay more for the sponsor’s product, with the sponsoring brand obtaining the highest market share. Prominent brands generally performed better than less prominent brands. The best–worst scaling method was also 35% more accurate in predicting brand choice than a purchase intention scale.
Research limitations/implications
Future research could use the same method to study other types of sponsors, such as title sponsors or other product categories.
Practical implications
Sponsorship managers can use this methodology to assess the return on investment in sponsorship engagement.
Originality/value
Prior sponsorship studies on brand equity tend to ignore market share or fans’ willingness to pay a price premium for a sponsor’s goods and services. However, these two measures are crucial in assessing the effectiveness of sponsorship. This study demonstrates how to conduct such an assessment using the BWDCE method. It provides a clearer picture of sponsorship in terms of its economic value, which is more managerially useful.
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Fatemeh Binesh, Amanda Mapel Belarmino, Jean-Pierre van der Rest, Ashok K. Singh and Carola Raab
This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.
Abstract
Purpose
This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.
Design/methodology/approach
Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.
Findings
The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.
Research limitations/implications
This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.
Practical implications
This study produced a reliable, accurate forecasting model considering risk and competitor behavior.
Theoretical implications
This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.
Originality/value
This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.
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Mengqiu Guo, Minhao Gu and Baofeng Huo
Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which…
Abstract
Purpose
Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.
Design/methodology/approach
We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.
Findings
We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.
Originality/value
In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.
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This research intends to investigate the determinants that affect consumers’ purchase intention of electric vehicles (EVs) in Malaysia using an extended theory of planned…
Abstract
Purpose
This research intends to investigate the determinants that affect consumers’ purchase intention of electric vehicles (EVs) in Malaysia using an extended theory of planned behaviour (TPB).
Design/methodology/approach
Survey data were collected with a sample size of 306. The research used SmartPLS 4.0 structural equation modelling tool to analyse the data. Reliability and validity tests (discriminant and convergent validity) were used and subsequently assessed the measurement and structural models. Mediation analysis was conducted to identify the role of the latent constructs.
Findings
The findings indicated that a green purchase attitude plays a complete mediation role in the effect of environmental knowledge on the purchase intention of EVs. In the same notion, the effect of price perception and availability of charging facilities on the purchase intention of EVs passes completely through perceived behavioural control. However, the subjective norm was an insignificant mediator of the impact between government support and EV purchase intention.
Research limitations/implications
This paper helps to examine the latent constructs that impact purchase intention using environmental knowledge, government support, price perception and the availability of charging facilities. Successful green marketing and a sustainable consumerism framework are seen as a booster to promote the usage of EVs in Malaysia.
Originality/value
An extended TPB model has been employed in this research to study the effects of the above-mentioned constructs. The results show that most of the extended constructs are significant in explaining the purchase intention. The empirical results address the gap in the consumer green attitude and provide insight into this area of study.
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Maneesha Singh and Tanuj Nandan
This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research…
Abstract
Purpose
This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.
Design/methodology/approach
Bibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.
Findings
The review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.
Originality/value
Over the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.
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