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The purpose of this paper is to present the results of surveys conducted in the field of level of e-commerce services quality. The criteria of quality of e-commerce services were identified. On this basis the hierarchy of importance of the adopted criteria for e-commerce service quality were proposed.

The level of customer satisfaction was measured using the Servqual method. In order to compare two groups: the quality of e-commerce services before purchase and the quality of e-commerce services after the purchase, a student’s t-test was used. To check if the relations between variables are sufficient to carry out the factor analysis (sampling adequacy), the Keizer–Meyer–Olkin test was used. The scope of the research included 23 selected criteria of customers satisfaction.

A comparison of the Servqual weighted and unweighted results shows that customers valued the guarantee/safety dimension the most. It can therefore be expected that customers perceive e-commerce services with increasing trust and consider them increasingly reliable which is also confirmed by the growing tendencies in the forecasts of e-commerce services in Poland.

Research allows to know the opinion and expectations related to the quality of services provided in the analysed area and to develop the strategy of company. The most important indicator of the quality of e-commerce services remains reliability (weighting = 0.34). However, the noticeable difference in opinions concerns the tangible elements index compared to the results of the Berry and Parasuraman team and amounted to 0.20.

Product verification and validation are integral to quality management. Product verification means verifying the conformity between a product’s actual and planned characteristics whereas validation means determining whether and to what extent it satisfies customers’ requirements. One of the key forms of product validation is testing with a group of customers. The purpose of this paper is to introduce a graphical method of product validation based on the Kano model.

The approach is based on a proposed method for categorising requirements based on a Kano questionnaire and then applies this method for the validation of a product – a website. The proposed method is based on three steps: graphical determination of requirements in a Kano model; determination of requirement fulfilment degree and prioritisation of corrective measures and improvements.

The study opens space for discussion of the potential for improving a product and methods for identifying critical faults in products. The proposed method also permits an assessment of the potential effectiveness of an improvement because it is able to quantify the effect of the product on the consumer resulting from a given quantity of effort. A case study demonstrated that the resulting priority of corrective measures and improvements was affected not only by the level of fulfilment of the requirements but also by the type, the most critical being non-fulfilment of must-be requirements.

The requirement curves are based on a verbal assessment of satisfaction in two states – if the requirement were fulfilled and if it were not fulfilled. The values of the start and end points may not be precise and could be affected by the natural character of subjective variables.

The proposed method is particularly suited to the initial testing of a product that is intended to lead to measures to eliminate customer dissatisfaction or increase their satisfaction – that is, to improve the product. The method also permits an assessment of the extent to which customers feel that their expectations have been satisfied and the effect that will be felt if the organisation decides to increase fulfilment.

The Kano model has not yet been applied to product validation, although it contains all the information necessary for this task. Knowing how satisfied customers are is an important part of product validation. At the same time, knowing a mechanism for “creating” this satisfaction is also very valuable information.

Pro-consumer refund system (PCRS) should be understood as a process in customer service, within which activities are related to the handling of goods that do not meet customer expectations, both in business-to-consumer (B2C) and business-to-business (B2B) relations. The research monitored three groups of variables – the importance of shopping decision factors, customer ID characteristics and PCRS characteristics. The authors explore relationships between these three groups of variables, and the authors tried to understand better the role of the PCRS system in customer perception of service quality.

An electronic survey was used to collect data in the planned structure. Research questions were developed into variables, and these were then the basis for creating questionnaires. Data were collected through electronic questionnaires. The sample consisted of 327 respondents from Poland (confidence level = 95%, confidence interval = 5.42).

The results of the research show that the PCRS is very important and appreciated from the customer's perspective. Most of the respondents are aware of their consumer rights and correctly understand the meaning of the term “pro-consumer refund system”. Respondents require complex service in terms of returns; their satisfaction does not depend on any individual factor. This also means that the return system must be lenient in each aspect.

A detailed analysis of aspects of PCRS has not yet been carried out in the literature. Although previous studies have focused, at least in part, on defining the essential attributes of PCRS, in most cases, it was an organization-driven view of this topic. The research examined the interrelationships between aspects of PCRS based on empirical data and offered a new perspective on this evolving concept.

The purpose of this paper is to propose a structured procedure for the capture and evaluation of innovative ideas in the early stages of product development. The procedure is designed to take account of internal and external factors affecting the value of innovative ideas.

The proposed procedure is based on divergent and convergent approaches to innovation. Ideas are generated and captured using targeted questions and subsequently evaluated using modifications of the Kano model and failure mode and effect analysis (FMEA). Idea evaluation considers four criteria – delight, originality, market share potential and simplicity – which are used to compute an “idea priority number”.

A case study looking at innovations in swimming goggles verified the validity of the proposed procedure. The procedure also supports fact-based decision making and applies a structured perspective to the innovation process that makes it easier to manage.

The case study made use of a pilot survey in which 32 customers participated. Although the case study was only intended as a demonstration of the method’s use, such a sample size could lead to unreliable results in certain cases.

Applications of standard or expanded FMEA do not add value to a product because the main purpose of the approach is to prevent failure. The proposed inversion of FMEA logic combined with customer view via the Kano model offers a method for the structured analysis of product innovations. No similar approach to the evaluation of innovations has so far appeared in the literature.

The purpose of this study is to present and explain a new customer segmentation approach inspired by failure mode and effect analysis (FMEA) which can help classify customers into more accurate segments.

The present study offers a look at the three most commonly used approaches to assessing customer loyalty:net promoter score, loyalty ladder and loyalty matrix. A survey on the quality of restaurant services compares the results of categorizing customers according to these three most frequently used approaches.

A new way of categorizing customers through loyalty priority number (LPN) is proposed. LPN was designed as a major segmentation criterion consisting of customer loyalty rate, frequency of purchase of products or services and value of purchases. Using the proposed approach allows to categorize customers into four more comprehensive groups: random, bronze, silver and gold – according to their loyalty and value to the organization.

Survey will bring a more accurate way of categorizing customers even in those sectors where transaction data are not available. More accurate customer categorization will enable organizations to use targeting tools more effectively and improve product positioning.

The most commonly used categorization approaches such as net promoter score, loyalty ladder or loyalty matrix offer relatively general information about customer groups. The present study combines the benefits of these approaches with the principles of FMEA. The case study not only made it possible to offer a view of the real application of the proposed approach but also made it possible to make a uniform comparison of the accuracy of customer categorization.

Comprehensive management systems such as ISO 9001 or ISO 14001 are designed to help organizations improve processes, ensure customer satisfaction, efficient information flow, efficient use of resources and many other prosperous management areas. These systems can also bring unintended direct and indirect effects on organizations. In this study, the authors examine the environmental effects that the implementation of these management systems cause.

A survey-based methodology was used for this study, with textile organizations in three countries – Poland, Slovakia and the Czech Republic. The research focused on four areas related to environmental effects. The first area was the level of improvement of the organizations' environmental performance, which was examined by the methods of descriptive statistics. The second area was analyzing differences in environmental effects concerning the implementation of the systems using inferential statistics. The third area was the analysis of latent links between individual effects using factor analysis.

This study's insights shed some light on the benefits of implementing more, not fewer systems with benefits to organizations and entire industries with new possibilities for economic growth that do not have to come at the expense of the environment.

Organizations implementing management systems can realize dynamic benefits across a supply chain and within a manufacturing organization. Here the authors see an opportunity for ISO systems as a stepping stone to a more sustainable textile manufacturing economy.

This bibliometric study provides an overview of research related to digital transformation (DT) in the tourism industry from 2013 to 2022. The goals of the research are as follows: (1) to identify the development of academic papers related to DT in the tourism industry, (2) to analyze dominant research topics and the development of research interest and research impact over time and (3) to analyze the change in research topics during the pandemic.

In this study, the authors processed 3,683 papers retrieved from the Web of Science and Scopus. The authors performed different types of bibliometric analyses to identify the development of papers related to DT in the tourism industry. To reveal latent topics, the authors implemented topic modeling based on latent Dirichlet allocation with Gibbs sampling.

The authors identified eight topics related to DT in the tourism industry: City and urban planning, Social media, Data analytics, Sustainable and economic development, Technology-based experience and interaction, Cultural heritage, Digital destination marketing and Smart tourism management. The authors also identified seven topics related to DT in the tourism industry during the Covid-19 pandemic; the largest ones are smart analytics, marketing strategies and sustainability.

To identify research topics and their development over time, the authors applied a novel methodological approach – a smart literature review. This machine learning approach is able to analyze a huge amount of documents. At the same time, it can also identify topics that would remain unrevealed by a standard bibliometric analysis.

The purpose of this paper is to develop a theoretical model that explains the impact of big data analytics capabilities (BDAC) on company's supply chain innovation capabilities and sustainable supply chain performance. BDAC is represented through two dimensions of big data technological capabilities (BDTC) and big data personal capabilities (BDPC). Moreover, the relationships between BDTC and BDPC with sustainable supply chain performance through the mediation effect of supply chain innovation capabilities are examined.

The study used a quantitative research approach. A survey of 400 Jordanian manufacturing companies was carried out to conduct this research. However, the responses of 207 managers were valid to be used in the analysis. In this study, the SmartPLS software was used to perform structural equation modeling using a partial least squares approach (PLS-SEM) and to examine the measurement and structural model's validity and reliability.

According to the results of this study, BDPC has a significant positive impact on supply chain innovation capabilities. Furthermore, the findings indicate that supply chain innovation capabilities are the most influential predictor of sustainable supply chain performance and act as a positive significant mediator in the relationship between BDPC and firm sustainable performance. Surprisingly, the study found that BDTC had no significant effect on supply chain innovation capabilities. Besides that, no significant relationship exists between BDTC and firm sustainable performance via the mediation effect of supply chain innovation capabilities.

This study provides an integrated research model that incorporates BDAC, supply chain innovation capabilities, and sustainable supply chain performance in order to analyze supply chain innovation and sustainable supply chain performance. This suggests that the scope of the study is broader in terms of predicting sustainable supply chain performance. As a result, the study intends to fill a gap in the literature by explaining how BDAC affects supply chain innovation capabilities and firms sustainable performance. In addition, the role of supply chain innovation capabilities as a mediator between BDAC and sustainable supply chain performance is investigated.

The aim of this paper is to examine how indoor aromatization affects the expressed and unexpressed satisfaction with the work environment in the production hall of an industrial company.

The aroma was flavored by an aromatization unit, the expressed satisfaction was measured on a scale and biometrics of facial recognition (FaceReader) was used to measure unexpressed satisfaction, enabling the recording of eight emotions and two basic emotions.

Research has shown the effect of aroma on two emotions – neutral and angry – which partially confirmed the sense of flavoring production facilities. Previous research has shown that positive feelings caused by a pleasant smell influence customers' purchasing decisions. As the use of aroma affects the mental state of the individual, it could be also applied for non-marketing purposes.

To date, there has been no research that systematically addresses the impact of aromatization on the perception of the work environment in a manufacturing company. The presented study is unique in its design and focus and provides basic information about the impact of aroma on individuals. The findings of this study can help to examine further aspects that indirectly affect performance.

This paper presents an approach by which potential benchmarking partners in the service sector can be matched together more efficiently. The purpose of this paper is to decide which organisations are appropriate partners based on their distinctive characteristics and problems with service management.

In the research presented in this paper, cluster analysis and other statistical analyses were applied to data from a survey of managers in service organisations with the aim of identifying groups of services related to each other in their distinctive characteristics and the problems they face.

The research found that it is possible to identify hidden “relationships” that allow superficially different services to be grouped together. The identified relationships are based on similarities in the problems which the companies face and their distinctive characteristics. Operating in a different area of activity increases the chance that a service provider will be willing to enter into a partnership and greater potential innovation value from best practice. Cluster analysis was used to identify three groups of services in the research sample which could be benchmarking partners for each other.

The research studied only a selective group of nine services in different areas of activity. A statistical survey of 388 organisations in one country verified the methodology in terms of statistical significance and the potential for successful identification and adoption of best practice within a group of related services created using the proposed procedure has also been confirmed. The real value of the approach can only be determined by its repeated use to establish benchmarking partnerships and the success of such partnerships, which can be defined as the adoption of innovative best practice.

The approach described in this paper could make it easier to develop non-competitive benchmarking in the service sector and increase the probability of success in identifying and transferring best practices between organisations in benchmarking partnerships established using it.

One of the first steps in collaborative benchmarking is to establish a partnership with a similar non-competing organisation. The procedure for this step is still not adequately defined. This paper contributes to the theoretical foundations and practical applications of research by setting out an original method for identifying suitable partners in non-competing sectors of the service industries. This will improve the prospects for successful partnership and greater innovativeness in best practice.