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Importance-performance analysis (IPA) is an effective tool for firms to prioritise service quality attributes, but has limitations in evaluating and enhancing service quality within a competitive environment. The purpose of this paper is to present an evolved model of IPA – importance-performance benchmark vectors (IPBV) – as a benchmarking tool and investigate its applicability in the context of hotel service quality.

Empirical studies based on self-completion survey data from 150 customers of two full-service hotels in Taiwan were conducted in to examine the practical utility of IPBV.

Eight key benchmark typologies were identified and expressed as vectors in the IPBV model which are as follows: “sustainable advantage”, “potential strength”, “false advantage or outstanding advantage”, “cease-fire competition”, “false disadvantage or on-hand disadvantage”, “potential weakness”, “dangerous warning” and “head-on competition”.

The paper extends the methodology to more cases, and other service industries to test further the discriminatory power of the model and to explore the descriptors in the IPBV vector model. Alternative seven-point or nine-point Likert scales could be explored to test the discriminant validity using means. The alternative IPA diagonal approach focussing on GAP analysis may reveal alternative interpretations for the IPBV vector model. Other extended models of IPA, which include competitor analysis, should be compared in practice using a data set where both quantitative and qualitative data could be generated.

The paper proposes the two-dimensional IPBV model which retains the advantages of IPA, but also includes competitor or benchmark comparisons which enable organisations to analyse their relative competitive position. The two-part model provides both quantitative information and qualitative interpretation of relativities. The graphical matrix models provide simple quantitative analysis of attributes, whilst the IPBV vector model provides qualitative interpretations of the eight competitive market positions. Vector analysis enables the development of competitive strategies relative to benchmarks, or within a competitive set. Importance is retained and means that organisations can benchmark against a range of competitors prioritising specific attributes for resource allocation.

The interpretive utility of the model should be explored with practitioners and decision makers in the service industries. The model has been designed for practical use in industry to inform operational and strategic decision making, its usefulness in practice should be explored and the attitudes of practitioners to the model should be tested.

Traditional approaches to benchmarking have adopted a one-dimensional approach that does not include a measure of the relative importance of the service quality dimensions in specific markets. This research develops a two-dimensional advanced model of IPA, called IPBV, which is based on vector relationships between key attributes of service quality. These vectors are explored and described in competitive terms and the model is discussed with regard to its implications for industry, practitioners and researchers.

Importance performance analysis (IPA) is a technique widely used to assist organisations in developing marketing strategies and improving products or service quality. Many scholars have revised IPA to augment its effectiveness. However, this involves some unknown problems that could lead organisations to make wrong decisions. This paper aims to look at this issue.

As a solution, this paper introduces Taguchi's signal‐to‐noise (S/N) ratio approach to treat ordered categorical data in analysing customer satisfaction and integrates it with gap analysis (GA) through S/N ratio to develop a modified IPA model. A Taiwan air‐conditioning manufacturer maintenance and repair service is illustrated to demonstrate the method.

According to the test case, the modified IPA model obtained more reliable results than the traditional IPA method, considering the central tendency and variance from different customer perceptions. The proposed method can determine exact marketing strategies and improvement directions for product or service quality attributes, reduce variance and (or) move performance to the target value.

This model overcomes the limitations of the traditional IPA model while retaining the merits of the traditional model. Using the modified IPA model an organisation can define its marketing strategies and take action to establish quality improvement activities. In other words, the organisation can avoid making wrong decisions when using the modified IPA model.

In the context of the Covid-19 pandemic and the trend in industrial development 4.0, the problem is how to conduct transactions of goods and services in the market using cashless payment in Vietnam, as in developed countries. This study aims to investigate, analyze and evaluate the factors affecting cashless payment behavior in Ho Chi Minh City, Vietnam.

The QR codes are used for payments because many factors affect the behavior of cashless payments made using electronic payment tools, including QR code tools. To achieve this goal, this study applied behavioral theory and the importance-performance analysis (IPA) model to measure service quality based on the difference between customer opinions on the importance and performance level of service providers’ targets. Survey results were obtained from 111 people living in HCMC, Vietnam, including 47 men and 64 women, which was a survey for 15 criteria.

According to the IPA results of the first quadrant, managers should focus on allocating their resources toward improving their performance across five key criteria. These criteria are crucial for meeting customers’ expectations and include factors such as product quality, responsiveness to customer queries or complaints, delivery times, pricing and customer service. In addition, the second quadrant of the IPA highlights another set of five criteria that perform well and are essential to the success of the business. These criteria could consist of customer loyalty, employee satisfaction, profitability, market share and innovation

These results provide a basis for solutions and recommendations for managers to refer to and apply consistent practices. Therefore, this study examines the cashless payment in Vietnam. Empirical results offer solutions to financial technology policy, marketing policy, cashless payment services and technology, which can help managers provide online payments using QR codes and contribute to monetary policy solutions.

This study aims to investigate the possible use of a deep neural network (DNN) as an inverse solver.

Different models based on DNNs are designed and proposed for the resolution of inverse electromagnetic problems either as fast solvers for the direct problem or as straightforward inverse problem solvers, with reference to the TEAM 25 benchmark problem for the sake of exemplification.

Using DNNs as straightforward inverse problem solvers has relevant advantages in terms of promptness but requires a careful treatment of the underlying problem ill-posedness.

This work is one of the first attempts to exploit DNNs for inverse problem resolution in low-frequency electromagnetism. Results on the TEAM 25 test problem show the potential effectiveness of the approach but also highlight the need for a careful choice of the training data set.

To analyze the limitations of two methods used in the identification of satisfaction attributes in products and services – importance performance analysis (IPA) and Kano method – and to propose a new method for identification of improvement opportunities based on the competitive analysis of the improvement gap.

A case analyzing attributes of the service “rodizio de pizzas” a kind of pizzeria found in Brazil, was used to illustrate the proposed method. Resulting from a focus group, four attributes, one of them being an innovation, were specifically chosen to include the different categories of the Kano model: basic, performance and excitement attributes. A survey was conducted with a random sample of 110 undergraduate students that eat regularly at pizzerias.

As a major limitation, IPA leads to different conclusions depending on how an attribute's importance is figured. Also, it does not take into consideration the non‐linear relationship between the performance of the attributes and customer satisfaction, possibly misleading improvement decisions and hindering the introduction of innovations. The Kano method identifies the non‐linear relationship between performance and satisfaction, but it does not take into consideration the current level of attributes' performance in the analysis. The proposed method successfully identified improvement opportunities in a service case, including the possible impact of including a new attribute, i.e. an innovative attribute, overcoming limitations of the IPA and of the Kano method.

The paper provides an intuitive and simple method that correctly identified improvement decisions in the case studied, including the introduction of an incremental innovation.

This research takes Taijiang National Park (TNP) tourists as the study population while gathering the survey data via an online questionnaire. For the data analyses, it uses the importance–performance analysis (IPA) and the Kano two-dimensional quality model to evaluate the tourist satisfaction of TNP. Specifically, it considers the importance of service quality, classifies its service quality attributes, and suggests the priority for service improvement, rendering the TNP valuable reference points to realign service strategies. The study shows that the service quality attributes related to service personnel are the priority item to be improved, which could eventually enhance tourist satisfaction. In addition, brand differentiation could be achieved by improving the attractive quality items identified in this study to enhance tourist loyalty.

The purpose of the study is to clarify the quality of home delivery logistics services from the perspectives of customers and provide insight to aid the prioritization of service quality improvements and guide managerial strategic planning.

The study used a three-dimensional model that integrated Kano model, goal difficulty (GD) and importance–performance analysis (IPA) for investigating service quality aspects emphasized by customers and determine which attributes should be prioritized according to an enterprise's resource and capability constraints. Data were collected through questionnaires administered to the customers and managers of five primary home delivery logistics service enterprises and six small to medium-sized enterprises in Taiwan. Improving the quality of home delivery logistics services has become of increased interest for enterprises.

The three most important attributes, ranked in order of priority for improvement, were the protection of customers' personal information, delivery of products without damage and reasonable compensation standards for product damage. The study concludes that enterprises should prioritize the improvement of these attributes. Implications, detailed explanations and directions for further investigations are also proposed.

The study discusses the importance and relevant satisfaction levels of service quality attributes from the perspective of customers while also considering the limitations of companies' resources and capabilities. The results indicate that the method can be used to identify service quality attributes of home delivery logistics and formulate strategies for enhancing customer satisfaction.

This study aims to purpose a strategy for Financial Technology (Fintech) service development to increase user adoption of Fintech services.

A conceptual model based on a risk-benefit approach was adopted based on the theory of reasoned action, the theory of planned behaviour and technology acceptance models. The partial least squares structural equation modelling method was used to test the proposed model and estimate the relationship between constructs. The results are used to develop strategies, which are then categorised based on the integration of an importance-performance analysis and the Kano model.

The results show that trust, economic benefit and convenience significantly influence users to adopt Fintech services, whereas privacy awareness, financial risk and legal risk factors affect user trust. A strategy for consumer protection against security threats and financial losses warrants the highest priority for improvement.

The findings of this study can help Fintech product managers classify their service improvements and help regulators make the appropriate policy decisions related to customer security and the adoption of Fintech.

There are some limitations of this research that should be noted. First, the research target respondents were millennials who have been statistically proven to have the highest affinity in using Fintech services. Second, the Fintech services used in this research were only mobile payments, peer-to-peer lending and crowdfunding. Future research could expand the number of research respondents to improve research validity, including other Fintech services or focus on one Fintech service at a time for targeted results and consider moderation variables, such as customer experience with Fintech services based on age and gender.

This study contributes to the development of new frameworks for evaluating Fintech adoption intention based on a risk-benefit approach. It also presents strategy recommendations to be implemented by Indonesian Fintech companies.

Based on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.

This study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.

Based on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.

In terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.

This study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

To enhance the transparency of the supply chain and ensure proper dissemination of information among the supply chain members in a timely manner, more and more companies are implementing supply chain information system (SCIS). Often the challenge among the organizations is how to go for a proper SCIS implementation and to identify the key performance indicators (KPIs) to evaluate the SCIS. The purpose of this paper is to provide a framework to evaluate the KPIs for SCIS of SCISs implementation from user’s perspectives.

In this paper, 16 KPIs were identified based on extensive literature survey. A fuzzy analytic hierarchy process (AHP) model is constructed to measure the users’ perceived importance and satisfaction for the KPIs. Subsequently, based on these two measurements, an importance-performance analysis (IPA) model along with a customer satisfaction attitude (SA) index is developed to categorize and prioritize the KPIs. As an empirical study, SCIS users across five industries belonging to different sectors were investigated to validate the model.

An IPA model along with a customer SA index is developed based on a fuzzy AHP model to evaluate the KPIs and provide the priorities of their improvement. Based on this result, some management implications and suggestions are proposed.

The study was limited to five organizations. More representative samples which can be sector specific can ensure better confirmation of the empirical results.

The KPIs identified in the research indicate the nature and dynamics of a complex SCIS implementation. It can serve as a checklist of areas that require attention when implementing a SCIS. The KPIs are presented through grouping in a systemic way. The development of the SAs in IPA model using fuzzy AHP is a novel approach.