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This study aims to widen the understanding of how remote work shapes the feedback environment by examining the perceptions of leaders and subordinates of daily, dyadic feedback interactions. The emphasis is on understanding how reciprocity within leader-member exchange (LMX) relationships manifests and how it influences the feedback dynamics.

Template analysis of a qualitative data set consisting of 81 semi-structured interviews with leaders (n = 29) and remote working subordinates (n = 52) was performed.

Drawing on the theoretical frameworks of the feedback environment and the leader-member exchange, the findings demonstrate the imbalance between the efforts of leaders and subordinates in building and maintaining a favourable feedback environment in the remote work context. The results of this study highlight the importance of the dyadic nature of feedback interactions, calling for a more proactive role from subordinates.

Given the estimation that the COVID-19 pandemic has permanently changed the way organizations work, leaders, subordinates and HR practitioners will benefit from advancing their understanding of the characteristics of dyadic, daily feedback interaction in remote work.

Qualitative research on feedback and leader-member exchange interactions in remote work that combines the perceptions of leaders and subordinates is sparse.

The purpose of this paper, applying concepts in the plant-based food sector, is a focus on the competitive rival trap for startup firms, with their initial advantage for under-served market segments, only to be overtaken by scale, speed, and brands of incumbent brand firms. As a case study of industry transformation, the food production sector illustrates how organizational innovation brings new forms of rivalry, from the farm gate to the kitchen plate. As a result, startups face a rivalry trap, if unable to scale quickly, as incumbents reframe their strategic response with startup acquisitions, corporate incubators or alliance partnerships consumer demand.

This paper outlines the features of precision agriculture, a new paradigm for agriculture and food production, requiring new competences and skillsets in the protein revolution, including issues like virus, bacteria and the molecular structure of food groups, animal breeding and veterinary medicine. Plant-based foods is used as a case study for startups and the rivalry trap.

The emergence of plant-based foods is a case study of market opportunity and creative destruction, where the potential market varies from $25bn to $72bn, and growing faster in the dairy sector. However, food incumbents bring new strategic responses and a rivalry trap, where startups must gain scale quickly in capabilities, talent and marketing prowess, often exploiting demand in market niches unimpeded by incumbent rivals.

Startups in biological sciences face massive challenges to increase scale and scope, even with unique intellectual property.

Startup firms need multidisciplinary management teams with a global outlook.

Plant-based foods form part of the protein revolution but face challenges of scale, cost competitiveness and taste, despite advantages for climate mitigation.

The impact of technological and science applications has blurred the traditional concept of industry boundary, with huge variations in the intangible knowledge component in their core activities and capabilities. Underlying variations imply that not all industries have similar supply demand conditions, with variations in input costs, capital intensity and innovation needs, with strategic implications for the rivalry trap.

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.