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Article
Publication date: 1 July 2009

Sven Theysohn, Oliver Hinz, Steve Nosworthy and Michael Kirchner

Preference analysis was conducted among supporter club members of the German national soccer team. Survey results based on 493 completed questionnaires underline the…

Abstract

Preference analysis was conducted among supporter club members of the German national soccer team. Survey results based on 493 completed questionnaires underline the market potential of official fan loyalty programmes due to a high average willingness to pay and a general preference for cheap and easy to implement 'right of first refusal' benefits for tickets as the main supporters club feature. Adequately designed supporters clubs may present soccer clubs with a new source of income while creating opportunities to improve stadium atmosphere and security.

Details

International Journal of Sports Marketing and Sponsorship, vol. 10 no. 4
Type: Research Article
ISSN: 1464-6668

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Article
Publication date: 1 June 2015

Zhaohua Deng, Shan Liu and Oliver Hinz

Although the health information seeking behavior of consumers through the internet has received great attention, limited attempt has been made to integrate both the health…

Abstract

Purpose

Although the health information seeking behavior of consumers through the internet has received great attention, limited attempt has been made to integrate both the health information seeking behavior and the usage behavior in a mobile online context. The purpose of this paper is to explore the factors that influence consumer mobile health information seeking (MHIS) and usage behavior based on information quality, perceived value, personal health value, and trust.

Design/methodology/approach

A survey was conducted to collect data. A two-step approach of structure equation modeling based was used to test the measurement model and hypothesis model.

Findings

Information quality, perceived value, and trust were found to have positive effects on both the intention to seek and to use health information, and that the intention to seek affects the intention to use. Among the three components of perceived value, the utilitarian and epistemic values were found to have significant effects on intention to seek. In addition, the current health status of health consumers moderates the relationships between MHIS and usage intention and their determinants.

Originality/value

Studies have primarily focussed on online health information seeking behavior, whereas a few of these studies have examined the seeking behavior intention and the usage behavior intention in a general model. The results indicate that health information usage behavior intention is closely related to the seeking behavior intention in the mobile context, which enriches the research on the relationship between information seeking and its outcomes. Furthermore, this study highlights the impact of information quality, perceived value, and trust on the intention to seek, and the impacts of information quality and trust on the intention to use, which have been overlooked in previous studies on MHIS.

Details

Information Technology & People, vol. 28 no. 2
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 5 February 2018

Chengxin Yin, Yan Guo, Jianguo Yang and Xiaoting Ren

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.

Abstract

Purpose

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.

Design/methodology/approach

By employing an innovative associative classification method, this paper is able to predict a customer’s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer’s characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop.

Findings

The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer’s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.

Originality/value

Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer’s satisfaction during the online while-recommending process.

Details

Industrial Management & Data Systems, vol. 118 no. 1
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 13 March 2017

Yan Guo, Minxi Wang and Xin Li

The purpose of this paper is to make the mobile e-commerce shopping more convenient and avoid information overload by a mobile e-commerce recommendation system using an…

Abstract

Purpose

The purpose of this paper is to make the mobile e-commerce shopping more convenient and avoid information overload by a mobile e-commerce recommendation system using an improved Apriori algorithm.

Design/methodology/approach

Combined with the characteristics of the mobile e-commerce, an improved Apriori algorithm was proposed and applied to the recommendation system. This paper makes products that are recommended to consumers valuable by improving the data mining efficiency. Finally, a Taobao online dress shop is used as an example to prove the effectiveness of an improved Apriori algorithm in the mobile e-commerce recommendation system.

Findings

The results of the experimental study clearly show that the mobile e-commerce recommendation system based on an improved Apriori algorithm increases the efficiency of data mining to achieve the unity of real time and recommendation accuracy.

Originality/value

The improved Apriori algorithm is applied in the mobile e-commerce recommendation system solving the limitation of the visual interface in a mobile terminal and the mass data that are continuously generated. The proposed recommendation system provides greater prediction accuracy than conventional systems in data mining.

Details

Industrial Management & Data Systems, vol. 117 no. 2
Type: Research Article
ISSN: 0263-5577

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Book part
Publication date: 20 August 2013

Simona D'Alessio and Steven Cowan

This chapter explores some of the complexities involved when undertaking research at an international level in the area of “inclusive” education and “special needs”…

Abstract

This chapter explores some of the complexities involved when undertaking research at an international level in the area of “inclusive” education and “special needs” education. The complexities encountered by researchers working in these fields, mirror many of the challenges that comparativists in education studies find themselves addressing. Drawing from earlier investigations and from reports by international organizations, this chapter highlights some of the dilemmas and challenges that researchers face when considering inclusion and special needs education in different countries. Differing interpretations of “inclusion” are discussed and then contrasted with thinking around “special needs” practices. The chapter moves forward to analyze how the adoption of differing theoretical frameworks can influence the way that “disability” is conceptualized and therefore how inclusive and special needs education are interpreted and then put into practice. The chapter argues that cross-cultural work opens up opportunities for further development and learning in this field. We further argue that such cross-cultural work can become a mechanism to instigate fundamental change in education.

Details

Annual Review of Comparative and International Education 2013
Type: Book
ISBN: 978-1-78190-694-1

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Article
Publication date: 14 September 2020

Rahul Kumar, Shubhadeep Mukherjee, Bipul Kumar and Pradip Kumar Bala

Colossal information is available in cyberspace from a variety of sources such as blogs, reviews, posts and feedback. The mentioned sources have helped in improving…

Abstract

Purpose

Colossal information is available in cyberspace from a variety of sources such as blogs, reviews, posts and feedback. The mentioned sources have helped in improving various business processes from product development to stock market development. This paper aims to transform this wealth of information in the online medium to economic wealth. Earlier approaches to investment decision-making are dominated by the analyst's recommendations. However, their credibility has been questioned for herding behavior, conflict of interest and favoring underwriter's firms. This study assumes that members of the online crowd who have been reliable, profitable and knowledgeable in the recent past will continue to be so soon.

Design/methodology/approach

The authors identify credible members as experts using multi-criteria decision-making tools. In this work, an alternative actionable investment strategy is proposed and demonstrated through a mock-up. The experimental prototype is divided into two phases: expert selection and investment.

Findings

The created portfolio is comparable and even profitable than several major global stock indices.

Practical implications

This work aims to benefit individual investors, investment managers and market onlookers.

Originality/value

This paper takes into account factors: the accuracy and trustworthiness of the sources of stock market recommendations. Earlier work in the area has focused solely intelligence of the analyst for the stock recommendation. To the best of the authors’ knowledge, this is the first time that the combined intelligence of the virtual investment communities has been considered to make stock market recommendations.

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Article
Publication date: 2 July 2020

Lucas Baier, Niklas Kühl, Ronny Schüritz and Gerhard Satzger

While the understanding of customer satisfaction is a key success factor for service enterprises, existing elicitation approaches suffer from several drawbacks such as…

Abstract

Purpose

While the understanding of customer satisfaction is a key success factor for service enterprises, existing elicitation approaches suffer from several drawbacks such as high manual effort or delayed availability. However, the rise of analytical methods allows for the automatic and instant analysis of encounter data captured during service delivery in order to identify unsatisfied customers.

Design/methodology/approach

Based on encounter data of 1,584 IT incidents in a real-world service use case, supervised machine learning models to predict unsatisfied customers are trained and evaluated.

Findings

We show that the identification of unsatisfied customers from encounter data is well feasible: via a logistic regression approach, we predict dissatisfied customers already with decent accuracy—a substantial improvement to the current situation of “flying blind”. In addition, we are able to quantify the impacts of key service elements on customer satisfaction.

Research limitations/implications

The possibility to understand the relationship between encounter data and customer satisfaction will offer ample opportunities to evaluate and expand existing service management theories.

Practical implications

Identifying dissatisfied customers from encounter data adds a valuable methodology to customer service management. Detecting unsatisfied customers already during the service encounter enables service providers to immediately address service failures, start recovery actions early and, thus, reduce customer attrition. In addition, providers will gain a deeper understanding of the relevant drivers of customer satisfaction informing future new service development.

Originality/value

This article proposes an extendable data-based approach to predict customer satisfaction in an automated, timely and cost-effective way. With increasing data availability, such AI-based approaches will spread quickly and unlock potential to gain important insights for service management.

Details

Journal of Service Management, vol. 32 no. 2
Type: Research Article
ISSN: 1757-5818

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Article
Publication date: 20 November 2019

Bahador Abolpour and Rahim Shamsoddini

Increasing the temperature of gas flows passing through hot tubes is one of the industrial interests. Operations in the gas phase with high temperature variations involve…

Abstract

Purpose

Increasing the temperature of gas flows passing through hot tubes is one of the industrial interests. Operations in the gas phase with high temperature variations involve engineers with the compressible fluids problems. The paper aims to discuss this issue.

Design/methodology/approach

In this study, a mathematical three-dimensional turbulent model is applied for investigating the heat transfer and laminar gas flow inside the thermal developing zone of a hot tube. The Favre Averaged Navier–Stokes and energy equations and also the Reynolds Stress Model are numerically solved to obtain the fluid velocity and temperature profiles inside this the tube. This model is validated using the experimental data and also well-known formulas in this science.

Findings

Finally, effects of inlet volumetric flow rate, heating conditions of the tube wall and tube angle on the temperature and velocity distributions of the gaseous phase inside this zone are investigated.

Originality/value

The compressible laminar gas flow and also heat transfer in the thermal developing zone of a hot tube is studied using a three-dimensional turbulent model.

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 3
Type: Research Article
ISSN: 1573-6105

Keywords

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Article
Publication date: 1 April 2012

Shawn Stevens and Philip J. Rosenberger

Sport has evolved into one of the largest industries in Australia and there is a corresponding increased interest in the factors influencing fan loyalty. This paper…

Abstract

Sport has evolved into one of the largest industries in Australia and there is a corresponding increased interest in the factors influencing fan loyalty. This paper presents a theoretically developed conceptual model which empirically tests the relationships between fan identification, sports involvement, following sport and fan loyalty. Survey results indicate that fan identification, following sport and involvement positively influence fan loyalty, while following sport was found to mediate the involvement-fan identification relationship.

Details

International Journal of Sports Marketing and Sponsorship, vol. 13 no. 3
Type: Research Article
ISSN: 1464-6668

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Article
Publication date: 1 October 2018

Huei-Wen Pao, Cheng-Yu Lee, Pi-Hui Chung and Hsueh-Liang Wu

The industry-wide adoption of a novel practice is often considered to be an institutional change. Although research on institutionalization has been accumulating, how and…

Abstract

Purpose

The industry-wide adoption of a novel practice is often considered to be an institutional change. Although research on institutionalization has been accumulating, how and why embedded actors in the field become motivated to embrace change that remains sidelined. Viewing the introduction of a new human resource management practice, the recruitment of non-compulsory certified manpower, which is still in its infancy in the service sector of Taiwan, as a new institution, the purpose of this paper is to identify the distinct motives behind firms’ hiring decisions, and examine the extent to which such hiring decisions are contingent on institutional conditions and firm attributes.

Design/methodology/approach

The data used to test the hypotheses were drawn from a survey on service firms in Taiwan in the second half of 2011. Hypotheses were examined through moderated hierarchical regression analyses in a sample of 254 Taiwanese service firms across major sectors.

Findings

Integrating the resource dependency and social contagion views, the study contends that resource scarcity drives, or legitimacy enables, service firms to deviate from traditional hiring patterns and instead adopt new preferences toward certified manpower. The study not only shows that social factors should be incorporated into the diffusion of a new HR recruitment practice in the service sector, which is traditionally based upon economic considerations, but also sheds light on the context-dependent nature of the process of institutional innovation.

Originality/value

This study is an attempt not only to test a dual-theoretical model on the extent to which a service firm’s new hiring pattern is influenced by two distinct types of motivation, but also to evidence how an institutional innovation, in terms of the regime of service manpower certification, takes root and spreads in the field. The managerially discretional account of the resource dependence theory needs to be reconciled with social contagion theory, which highlights the influence of collective actions and so provides a better understanding of the diffusion of new HR recruitment practices in the service industry.

Details

Journal of Advances in Management Research, vol. 15 no. 4
Type: Research Article
ISSN: 0972-7981

Keywords

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