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This study aims to integrate the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method with quality function deployment (QFD) which helps to improve the weight of technical attributes by calculating the closeness of particular attributes with the best attributes and farthest from the worst technical attributes simultaneously.

For the fulfilment of the aim of the study, detailed literature is reviewed and a suitable tool for score calculation has been selected. Further, the proposed methodology is applied in a literature-based case study, and a new weight is calculated and compared with the previous weight.

The finding of the study suggests that higher weightage is assigned to those technical attributes which is very close to the best technical attribute, and lower weightage is assigned to the technical attributes which are very close to worst technical attributes. Therefore, the weight calculated with the help of the proposed methodology will suggest to optimally invest the resources on technical attributes so that the maximum customer satisfaction is achieved.

The proposed method will help in better score calculation of QFD. Therefore, the use of the proposed method will help in better product and service design for maximum customer satisfaction.

Proposed methodology aims to help managers, administrators, QFD practitioners and product/service designers to design a new product/service or mange the quality of existing product/services in an effective way.

This is the first kind of study, in which modification in score calculation has been proposed. This modification will help in the better assignment of resources for maximum customer satisfaction.

Data has become a factor of production. This occurs when history enters the era of big data, in which technologies such as artificial intelligence, cloud computing and blockchain are used to collect, manipulate, mine and process data. Data is a special product of labor, a sub-derivative of other production factors.

The data factor has a dual attribute: being physical (technical) and social. The social attribute of the data factor can not only materialize the technical attribute but also amplify it. In other words, the data has a multiplication effect on the allocation efficiency of other production factors. The social attribute of the data is brought out via the technical attribute as the medium. From a technical perspective, this medium is strongly adhesive, and after being bonded with other factors of production, it will only lead to a physical reaction and not change the nature of other factors.

However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

Therefore, to get a scientific understanding of the dual attribute and its interaction effects on the data factor, it is necessary to take the following steps. We should promote institutional design that amplifies the positive externality, with a focus on facilitating public data sharing and improving the value of commercial data development. Also, we need to strengthen institutional arrangements that prevent and control the negative externality by emphasizing data supervision based on data types and levels as well as the rule of law.

This paper aims to propose and test an exploratory model, illustrating performance differences based on underlying role identities and attributions of salespeople in business markets.

The sample consists of 60 salespeople from a Fortune 100 high technology firm responsible for managing multi‐million dollar customer projects. Interviews with both salespeople and their sales managers provided the data to examine the relationships among role identities, attributions, and performance.

The model suggests that higher‐performing salespeople have role identities as sales consultants, whereas lower performers tend to have role identities as technical specialists. Further, those salespeople with sales consultant role identities were more likely to attribute success to relational factors, whereas salespeople with technical specialist role identities were more likely to attribute success to technical factors. There were no significant relationships among role identities and attribution type in unsuccessful customer engagements.

While multiple sources of data were obtained from both salespeople and sales managers, all the respondents were from one large multinational organization.

The link between role identity and attributions provides opportunities for situation‐based sales training programs, and sheds new light on performance differences among salespeople.

The paper isolates role identity as a potential driver of salesperson performance.

Empirically investigates, using a conjoint methodology, the importance weights given the attributes of quality for acute care hospital services. The study shows consumers evaluated the technical dimensions of nursing care, physician care, and outcome as more important than the accommodation functions of hospital care, and there are significant interactions among the technical dimensions. Both sets of dimensions were important and significant, but technical quality evaluations were not influenced by the perceived quality level of the affective attributes. The relative importance of these attributes were quite stable among various subgroups of past patients.

Sports organisations must continuously assess how better to meet or exceed consumer expectations and perceptions of their experience in order to maintain and increase the number of spectators and loyal fans attending their sporting events. This study aims to enhance our understanding of which characteristics of a service attribute will best define its quality and impact on spectator behaviour by understanding the causal relationship between perceived service quality (PSQ) and satisfaction.

This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.

Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.

This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.

This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.

Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

This paper focuses on customer value analysis and measurement, framing customer value management as one of the main antecedents of the company value-creation process. The paper builds on three main pillars. First, the paper highlights the critical role of customer value in business-to-business markets, focusing on the links between the company's ability to manage customer value-creation processes and the positive financial and economic outcomes generated by loyalty effects. Secondly, the paper develops key analytical stages for an understanding of customer value. The focus is on the customer value-chain concept, including consideration of the customer information and acquisition process and its decision rules. Third, the paper illustrates the measurement process, offering an organizational framework for selecting the most suitable method for measuring perceived customer value. The methodological alternatives range from desk measures (e.g., technical computation of the total cost of ownership (TCO)) to field analysis, like those considered under both compositional and the decomposition approaches (e.g., conjoint analysis). The paper concludes with remarks on the managerial implications of these measures, as well as offering suggestions for further research on value for the customer.

This paper presents an integrated framework for the selection of attributes used in the evaluation of advanced manufacturing systems. The primary focus in the development of this framework is the modularity of the framework so that it is applicable to a wide range of advanced manufacturing systems with differing process configurations and technologies. Based on data collected from industry and the current body of knowledge, decision attributes were identified and ranked relatively against each other, forming a hierarchy of decision attributes. To simplify the hierarchy, making it more user‐friendly in real‐world applications, each decision attribute was also evaluated relative to the strength of its relationships to other decision attributes. Several decision attributes were found to be highly correlated with others, resulting in a new, single decision attribute. The final decision attribute hierarchy provides managers responsible for making capital decisions involving advanced manufacturing technologies with a framework for their decision making.

The purpose of this paper is to determine the requirements of accounting graduates in relation to generic attributes. Employers have consistently maintained that graduates are deficient in this area. This Australia‐wide, all‐sector study addresses the issue by examining what employers mean when they make demands for universities and academics to deliver work‐ready graduates.

Interviews (recorded, transcribed and analysed with NVivo) with employers, and accounting professional bodies were conducted to ascertain their views of their needs of accounting graduates into the future.

Employers held the generic attributes of communication, team work and self‐management to be the most critical for graduates in the three areas of recruitment, training and ongoing employment. Demands on universities to deliver work‐ready graduates are not homogeneous. Employers in different sectors construe the meaning of generic attributes in line with their specific needs.

The study was an original piece of work that gauged the opinions of professional accounting bodies and employers of accounting graduates across Australia and in all sectors of the accounting profession. The value of the study is to inform academics as to the ranked importance of generic attributes but also alert them to the different meanings that are assigned to these skills by employers in different sectors.

Small-medium enterprise (SME) service industry is an industry that continues to experience growth in developed and developing countries, including Indonesia. SME service industry that engaged in the service industry, namely, rental for generator set, air conditioner and sound system. In recent years, this SME has been experienced in declining in sales and getting some complaints from their customers. Many studies suggest that service quality and customer satisfaction are the key factors in the service industry. The purpose of this paper is to analyze the quality of service based on the customer’s perspective.

Data was collected using a combination of literature review, interview, brainstorming and questionnaires and analyzed by using importance-performance analysis (IPA) and quality function deployment (QFD) model.

This research resulted in nine technical requirements that allow the company to focus on these attributes to help the company enhance its customer satisfaction.

Based on the theory, applying service quality, IPA and also QFD will result in customer satisfaction. Practically the enhancement in customer satisfaction is not as easy as expected. Nowadays, customers always expect more and more and it is impossible to fully captured customers’ needs and always satisfy customers. Nevertheless, for this research company can understand their customers better, companies can evaluate their performances based on the customers’ perspective and know their customers’ needs. The company also know their strengths and weaknesses to allocate the resources and maximize their potential. Last but not least, the company is able to know their strategic priority that needs to be done for their better performance in the future to fulfill their customers’ needs and hope to enhance their customer satisfaction

A lot of research about customer satisfaction but still limited especially in the service industry in Indonesia using a combination of IPA and QFD model. So this research will give benefit for SMEs in Indonesia to allocate their resources more effectively by looking at the results of the four quadrants of IPA and house of quality (HOQ) framework can be used for a company as the references for their priority strategic option. Yet, to keep improving, the company recommended reviewing HOQ periodically.