Assessment of residential institute foodservice using Kano categorization and importance–performance analysis

The effects of chatbots’ attributes on customer relationships with brands: PLS-SEM and importance–performance map analysis

Purpose

Many firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these efforts. Chatbots are types of virtual-assistant software programs that interact with users through speech or text. This paper aims to investigate whether the perceived hedonic and utilitarian attributes of chatbots can influence customer satisfaction and, consequently, their relationships with brands.

Design/methodology/approach

Data were collected through a questionnaire-based survey among a sample of Italian consumers. A convenience sampling technique was used. Data were then analyzed through Partial Least Squares Structural Equation Modeling to provide a prediction-oriented model assessment. The findings were then complemented with an importance–performance map analysis (IPMA) to gain more detailed insights and actionable guidelines for managers.

Findings

The findings highlighted that the perceived hedonic and utilitarian attributes of chatbots positively influenced customer satisfaction and improved customer relationships with the brands. However, the IMPA highlighted that the performance levels of two most important attributes – system quality and experience with chatbot – could be improved resulting in additional improvements of customer satisfaction.

Practical implications

This study suggests the importance of firms’ investments in and adoption of e-agents to strengthen consumer–brand relationships and of considering both the hedonic and utilitarian attributes of their e-agents.

Originality/value

This article attempts to enrich and consolidate the growing body of literature concerning the impacts of new technologies – and, specifically, chatbots – in service marketing.

A Study on the Factors Affecting Customer Satisfaction with Institutional Foodservice during COVID-19

This study used a mixed-methods design combining qualitative and quantitative research to understand the factors affecting customer satisfaction with institutional foodservice during COVID-19. First, in-depth interviews and open coding were conducted with institutional foodservice users, and they indicated that harmonious menu composition, food taste, food temperature, close proximity to the restaurant, clean tableware, staff hygiene, hand sanitizer use, and table dividers were important concepts (qualities). Second, factors affecting customer satisfaction and dissatisfaction with institutional foodservice were analyzed using the Kano model, customer satisfaction coefficient, and importance–satisfaction analysis. The highest priorities derived from those analyses for improving the quality of institutional foodservice were harmonious menu composition and food temperature. This mixed-methods study is meaningful because it comprehensively analyzes the satisfaction factors important to customers of institutional foodservice, which have changed because of COVID-19. Therefore, these results will help to improve institutional foodservice and industrial development.

Evaluation of machine tool substitute under data-driven quality management system: a hybrid decision-making approach

Purpose

Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.

Design/methodology/approach

In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.

Findings

The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.

Research limitations/implications

The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.

Originality/value

The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.