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This study examines whether certification improves the dimensions of total quality management (TQM) and whether the impact of certification is similar across companies of different sizes and industries. The benefits of certification for companies have been widely discussed in recent years. The general debate has been partly marked by the dispute about whether companies will benefit more from certification or the implementation of TQM. This debate has led to numerous studies on the benefits of certification; however, few studies simultaneously have examined traditional TQM issues and the requirements of the new quality standard, ISO 9001: 2015, as well as the updated European Foundation for Quality Management (EFQM) criteria.

This study was conducted via a survey of Finnish SMEs and covered both industrial and service companies. The study comprehensively compared industrial companies with service companies and small companies with medium-sized companies.

In industrial and small enterprises, certification clearly has a positive effect on the dimensions of TQM, but a similar effect was not observed in medium-sized enterprises or in the service sector.

This is one of the first studies to examine the effect of certification on TQM in different types of SMEs while simultaneously considering EFQM and ISO 9001:2015 in Finland. The significant originality of this research lies in the formation of a comprehensive research framework for the dimensions of TQM.

This study evaluates a multidimensional hierarchical scale of smart policing service quality.

Qualitative and quantitative analysis tools were used to develop a smart policing service quality scale based on the integrative psychometric scale development methodology. A multidimensional hierarchical structure was proposed for smart policing service quality; a group of preliminary items selected from literature was used for the qualitative analysis. For data collection, users of smart policing services were selected through the United Arab Emirates (UAE) research centre. Several statistical methods were employed to verify reliability and validity of the construct and nomological validity of the proposed scale.

A smart policing service quality scale of 23 items was developed based on a hierarchical factor model structure. Nomological testing indicated that overall smart policing service quality is positive and significant, thus contributing to user satisfaction, intention to continue using the system and enhanced quality of life.

This study enables managers to evaluate types of policing quality and effectively implement strategies to address security and sustainability issues that exist currently in smart services.

Previous studies on policing service quality have not sufficiently addressed the role of smart policing service quality; the nature of discussion in this area is primarily based around concepts. The development of the smart policing service quality scale provides a measurement tool for researchers to use to enhance the understanding of smart policing service quality.

This study aims to empirically investigate the effects of both soft and hard quality management (QM) on innovation and organizational performance. It also examines the mediating role of hard QM, administrative innovation and technical innovation on the relationship between soft QM and organizational performance in higher education (HE).

The approach of this study is quantitative. The data used to test the hypotheses were obtained through online questionnaire sent to the academic staff of public universities in Naples (Italy). The hypothesized relationships are tested with data collected from 356 respondents by using the partial least squares structural equation modeling technique (PLS-SEM).

The results show that quality practices improve innovation and organizational performance, while innovation positively impacts organizational performance. The findings also indicate that soft QM affects organizational performance directly and indirectly through hard QM. Hard QM and innovation show a partial sequential mediating effect on soft QM-performance relationship

In order to implement quality management properly in HE, directors need to recognize the different roles that soft and hard QM can have on innovation and organizational performance. It is important that higher education institutions (HEIs) allocate resources to establish both types of QM practices to achieve the effectiveness of the whole QM system.

Despite the existence of numerous studies on the relationship between QM, innovation and organizational performance in manufacturing and services, studies conducted in higher education are still few. This is one of the earliest studies that adopt the multidimensional approach of QM in HE which could help directors understand the interdependencies and different roles of soft and hard quality practices.

This paper covers the development of a multidimensional contract administration performance model (CAPM) for construction projects. The proposed CAPM is intended to be used by the industry stakeholders to measure the construction contract administration (CCA) performance and identify the strengths and weaknesses of the CCA system for running or completed projects.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. In the first phase, contract administration indicators were collected from relevant literature. In the second phase, an online questionnaire was prepared, and data were collected and analyzed using the crisp value of fuzzy membership function, and structural equation modeling (SEM). The fuzzy set was chosen for this study due to the presence of uncertainty and fuzziness associated with the importance of several key indicators affecting the CCA performance. Finally, SEM was used to test and analyze interrelationships among constructs of CCA performance.

The data collected from 336 construction professionals worldwide through an online survey was utilized to develop the fuzzy structural equation model. The goodness-of-fit and reliability tests validated the model. The study concluded a significant correlation between CCA performance, CCA operational indicators, and the process groups.

The contribution of this paper to the existing knowledge is the development of a fuzzy structural equation model that serves as a measurement tool for the contract administration performance. This is the first quantitative structural equation model to capture contract administration performance. The model consists of 93 Construction Contract Administration(CCA) performance indicators categorized into 11 project management process groups namely: project governance and start-up; team management; communication and relationship management; quality and acceptance management; performance monitoring and reporting management; document and record management; financial management; changes and control management; claims and dispute resolution management; contract risk management and contract closeout management.

Rooting in the literature on training and laying on Kirkpatrick model, this paper aims to explore key drivers of corporate training to identify how they can be combined into an integrated framework of learning for human capital development.

By adopting the constructivist grounded theory, this contribution analyzes the experience carried out in the last ten years by Virvelle, an Italian corporate training firm.

Results show the rise of five core categories, g1iving rise to an integrated model of Kirkpatrick. Their dynamic interplay led to a new orientation of Kirkpatrick model giving rise to a metalearning ecosystem.

Managerial implications have identified key factors on which building and implementing appropriate corporate training programmes capable of triggering co-generative processes of value creation. Particularly, the essential role of learning quality culture, digital technology and personalization are detected in integrating not only hard but furthermore soft shades of learning. Concerning theoretical implications, the emergence of key structural and systems enabling dimensions for learning, and contextual mechanisms involved in reshaping training effectiveness and achieving integrated learning outcomes are detected. The main limitation of this study lies in the need to generalize results: the conceptualized framework needs to be empirically tested.

The value of this research is built along three main points. The first is the integration among the core categories that an integrated learning system can be built on, promoting learning quality culture through positive feedback loops. The second is represented by the chance to enhance an integrated mutual knowledge development among engaged actors, thereby shaping a more holistic and multidimensional learning model. The third is related to the transversal role that digital technology plays in all phases of the training process as it integrates and enriches them.

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

The purpose of this study was to review existing healthcare service quality-measurement models.

A review of the literature was conducted utilizing keywords “healthcare’’, “service quality’’, “measurement models”, “SERVQUAL”, “SERVPERF”, “HEALTHQUAL”, “PubHosQual” and “HospitalQual”. These investigations were selected from the “Emerald’’, “ABI/Inform”, “ScienceDirect” and “EBSCOhost” databases. A range of studies used in the makeup of the healthcare quality-measurement model for a 36 years period (1979 to 2015) were examined in an exhaustive survey of the literature. Of 137 studies reviewed, 74 studies were selected for analysis.

As yet, no consensus has been reached among scholars on the definition and indicators and factors of the quality of the healthcare services. Moreover, most of the current models are of Western origin and incongruent with the cultural and economic contexts of developing countries. The previous studies create scales resembling the generic measures of service quality, which may not be completely appropriate for assessing the perceived quality of healthcare services. Furthermore, previous studies were too narrow, overemphasizing the quality of healthcare only as far as the functional aspect of the services were concerned and paying too little attention to the technical aspects, using the experience of healthcare providers. These results have much room for failures. This is therefore advising healthcare organizations that need to develop their own models for measuring the quality of their services.

Generic models no longer suffice in measuring the quality of healthcare services. Developing countries should try and develop their own models for measuring the quality of healthcare services.

Customer experience has become a vital premise in service theory and practice. Despite researchers' and managers' growing interest, the customer experience remains a complex and multidimensional concept that is challenging for service providers to understand. This study aims to graph the experience in its multidimensionality by categorizing and proposing matching practices for service marketing managers to channel and foster customer experiences in customer journeys.

To support the predominantly conceptual nature of the study, an abductive approach underpinned by the authors' vast experience in academia and practice, real-life autohermeneutic phenomenological experience tales and theory on customer experience and its management by providers is deployed to craft a model that addresses and highlights the multidimensionality of experience.

This study introduces the “GraphEx” (Graph Experience) hip-pocket model, which expresses customer experience in a simple yet multidimensional fashion and offers managerial practices to foster the customer's experience. The model contains three dimensions (valence, type of experience and visceral intensity) and five managerial practices (urgent patchwork, restoring, activating and stimulating desire, bolstering and safeguarding appreciation).

This study contributes to the service literature by creating granularity in the multidimensionality of customer experience. This study advances customer experience management in practice by providing service managers with novel possibilities for understanding and managing customer experiences intelligently. This can help service providers streamline and innovate customer experience strategies during customer journeys and foster customer loyalty.

Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.

The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.

The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.

The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.

The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.

The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.

The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.