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This study aims to construct a scale and identify the factors that might affect the implementation of gamification and Bloom's Digital Taxonomy-based assessment of students' learning, guided by the Goal-Setting Theory.

This study used a sequential exploratory mixed-methods design where data were collected qualitatively via interviews (n = 18) and field notes. Quantitative analysis was then applied via questionnaires (n = 96).

Four major themes emerged following thematic analysis of the observation notes and interview data: learning engagements; understandable learning goals; friendly competitions; and interactive learning feedback. A scale consisting of 32 items was developed based on the qualitative data. The quantitative data were then collected to evaluate the scale's factor structure using maximum likelihood exploratory factor analysis with Promax factor rotation. The final version of the scale had 29 items. The authors verified the alpha coefficients for each element and the entire hierarchy, ranging from 0.94 to 0.98 for the factors. The total scale was determined to be 0.96, and the Item Content Validity Index was considered valid.

The scale developed in this study is expected to inform future research and guide educators who wish to incorporate contemporary digital pedagogies in a different context. This study could also be beneficial to researchers who aspire to perform research on Goal-Setting Theory in the educational context.

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 construct models to classify independent smallholder farmers’ (ISFs) plantation suitability and its competitiveness index. It proposes the models with the objective to accommodate ISFs as the main source of raw material for the palm oil industry. It was predicted that the supply of oil palm fresh fruit bunch would depend on ISFs’ plantations due to the government policy that restricts the expansion of the plantations.

The study was designed using a geographic information system approach and analytical hierarchy process for mapping the suitability of smallholder farmers’ oil palm plantation in the Kampar Regency. The competitiveness index was measured using a modified Diamond Porter framework and competitiveness index quantification. The model was conducted on 177 respondents from five districts in Kampar Regency.

The results indicated that it mapped 128,936.759 hectares area of ISFs’ oil palm plantation in the Kampar Regency. The results of plantation suitability showed that only 13.88% of plantations owned by ISFs were potential, 71.21% of them were in the developing category and 14.91% of plantations were non-potential. The competitiveness index showed there were only 7.91% of them at the developed competitive position, 73.45% at developing a competitive position and 18.64% at the least-developed position.

The paper includes implications for developing ISFs’ capacity building and best practice management for oil palm optimization, resulting in bargaining positions and social well-being.

The study had succeeded to visualize ISFs’ plantation area suitability and competitiveness at Kampar Regency, Riau Province. The model provides a brisk understanding and valuable information about ISFs’ conditions spatially. It offers specific outcomes and becomes important in optimize and develop the existing plantations at the right time and exact location.