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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 editorial for the 6th World Conference on Production and Operations Management (P&OM) 2022 Special Issue delves into the transformative role of advanced artificial intelligence (AI)-driven chatbots in reshaping operations, supply chain management and logistics (OSCM). It aligns with the conference’s theme of exploring the intersection between P&OM and strategy during the Technological Revolution.

Utilizing a conceptual approach, this paper introduces the “ERI Framework,” a tool designed to evaluate the impact of AI-driven chatbots in three critical operational dimensions: efficiency (E), responsiveness (R) and intelligence (I). This framework is grounded in disruptive debottlenecking theory and real-world applications, offering a novel structure for analysis.

The conceptual analysis suggests immediate benefits of chatbots in enhancing decision-making and resource allocation, thereby alleviating operational bottlenecks. However, it sees challenges such as workforce adaptation and potential impacts on creativity and sustainability.

The paper suggests that while chatbots present opportunities for optimizing operational processes, organizations must thoughtfully address the emerging challenges to maintain productivity and foster innovation. Strategic implementation and employee training are highlighted as key factors for successful integration.

Bridging the gap between the burgeoning proliferation of chatbots and their practical implications in OSCM, this paper offers a first perspective on the role of AI chatbots in modern business environments. By providing insights into both the benefits and challenges of chatbot integration, it offers a preliminary view essential for academics and practitioners in the digital age.

This study aims to investigate ChatGPT’s potential in environmental education concerning sustainable development goals. Heuristic evaluation and usability testing identify critical usability issues, including inadequate multimedia support, language barriers and insufficient fact-checking capabilities.

The study uses heuristic evaluation and usability testing to assess ChatGPT’s efficacy in environmental education at a Chinese higher education institution. The evaluation identifies essential limitations, including reliance on text-only resources, absence of multimedia assets, technical deficiencies, language barriers, lack of fact-checking tools, context-related issues, delayed information, inconsistency and limited expertise. Data was collected through quantitative and qualitative analysis, with input from experts and students.

Findings suggest that while ChatGPT offers opportunities for interactive learning, its limitations hinder comprehensive educational outcomes. A proposed hybrid model combining generative AI and human elements aims to enhance engagement and learning effectiveness. This research offers a foundation for integrating AI tools into environmental education, addressing usability gaps and fostering sustainable learning environments.

This research contributes to a deeper understanding of the role of artificial intelligence in environmental education and underscores the importance of incorporating human intervention. The proposed hybrid approach offers a framework for creating more comprehensive and meaningful learning environments by leveraging the unique strengths of human engagement alongside generative AI technology.