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Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

This study aims to examine the relation between error management culture and restaurant employee promotive and prohibitive voices. Drawing on socially desirable responding theory, the authors also propose a dual-mediation mechanism underlying the impact of error management culture on employee voice: psychological empowerment, as the agentic motive, and psychological safety, as the communal motive.

The authors recruited 223 participants working in 37 restaurants in China for the two-wave surveys with a one-week interval. The authors use a multilevel modeling paradigm to test the study hypotheses.

This research examines a multilevel model suggesting that error management culture can boost employee promotive voice and prohibitive voice via the mechanisms of psychological safety and empowerment. In addition, the results suggest that psychological empowerment (vs psychological safety) has a strong mediation effect between error management culture and promotive voice, but the authors find no difference in mediating effects between error management culture and prohibitive voice.

Restaurants can encourage employee voice by developing and maintaining an error management culture. Organizations can also consider motivating employees from both agentic and communal perspectives. Moreover, managers should focus more on empowering employees in areas characterized by Confucianism or collectivism.

The current research adds to the voice literature by identifying an organizational cultural antecedent of employee voice–error management culture. Agentic and communal motives are two motivational paths of employee voice. It also extends the social desirability theory by highlighting the role of the agentic motive in the Chinese restaurant context.

This research attempted to establish the underlying dimensions of supply chain management practices, blockchain technology and supply chain performance in the Indian dairy industry. Additionally, the study proposes a conceptual model that shows the mediating effects of blockchain technology in the relationship between supply chain management practices and supply chain performance.

Structural equation modelling (SEM) is incorporated to examine the proposed model using SPSS and AMOS version 24. The study population includes 119 registered Indian dairy processing units operating in Uttar Pradesh and New Delhi (source: Dairy – India). Individual registered dairy processing unit's top four executives, that is Head of the Dairy Processing Plant, Supply Chain head and Marketing Head, and IT head are chosen as the respondents of the study, which renders the sample size of 476. Judgmental sampling based on the organisation's market position and plant production capacity (i.e. one lakh litre per day) has been set as the benchmark for selecting the dairy processing units. The executives are selected as respondents as they are well-versed in the phenomenon of supply chain management practices, blockchain technology and supply chain performance compared to other staff working in the dairy industry. The data was collected from December 2021 to March 2022 through judgmental sampling. The target sample size was 476, but only 286 questionnaires were received in a completed state and were further used for analysis.

Manufacturing practices, information sharing, distribution management, inventory management and blockchain technology have a significant and positive impact on supply chain performance in the Indian dairy industry. Furthermore, the research demonstrates that blockchain technology partially mediates the relationship between supply chain management practices and supply chain performance in the context of the Indian dairy industry.

This research is focused on the Indian dairy industry operating in only two states, namely New Delhi and Uttar Pradesh. More research is needed to determine whether SCM practices and the prospects for blockchain technology among channel members are universally applicable to merchants in non-dairy products. Similar investigations should be carried out on dairy industry operating in various formats and in numerous geographic locations. Further, case studies can be conducted by future researchers to learn how supply chain management methods are deployed, what precisely these practices entail and what costs and time demands are required by these practices in context of small independent retailers across different germane expanse.

While the available literature on the research area is spread out, the influence of blockchain technology in the Indian dairy industry has not yet been sufficiently analysed. Therefore, the research article focused on exploring underlying dimensions of the constructs of supply chain management practices, blockchain technology adoption and supply chain performance in the context of the Indian dairy industry.

Food safety management systems (FSMSs) are implemented in food supply chains primarily to adhere to regulations as well as meet customer requirements. The literature contains examples of successful and failed implementation of FSMSs, including the influencing factors. This paper aims to explore the literature on the effectiveness factors of FSMSs to identify the literature findings, the emerging themes and suggestions for future research.

A systematic literature review (SLR) is used to synthesise research on the factors influencing the effectiveness of FSMSs. The methodology consists of formulating the research questions, identifying, selecting and evaluating relevant studies, analysing, synthesising and presenting findings.

The effectiveness factors of FSMSs identified from the literature are clustered into five categories, namely (1) FSMS culture; (2) FSMS inspection, verification and audit; (3) FSMS knowledge; (4) Legal regulations; and (5) Prerequisite programmes. Moreover, it was determined that the effectiveness factors featured in a variety of contexts.

SLR is an objective, rigorous and reliable approach to exploring the effectiveness factors of FSMSs. However, the results are contingent on research studies selected for review, which depends on the research criteria used, available and accessible research studies and the criteria for inclusion and exclusion of studies. This dependency introduces bias, an intrinsic limitation of the SLR approach.

In this study, the effectiveness factors of FSMSs are identified utilising an SLR approach, integrating findings from previously reported research. The factors and resulting emerging themes identified in this study are beneficial, including in improving food safety management practices.

The growing awareness of climate risks associated with food safety issues has drawn the attention of stakeholders urging the food industry to carry out a sustainable food safety management system (FSMS). This study aims to investigate whether the critical success factors (CSFs) of sustainable FSMS can contribute to achieving climate neutrality, and how the adoption of FSMS 4.0 supported by the Industry Revolution 4.0 (IR 4.0) technologies moderates the impact of the CSFs on achieving climate neutrality.

Survey data from 255 food production firms in China and Vietnam were utilised for the empirical analysis. The research hypotheses were examined using structural equations modelling (SEM) with route analysis and bootstrapping techniques.

The results show that top management support, human resource management, infrastructure and integration appear as the significant CSFs that directly impact food production firms in achieving climate neutrality. Moreover, the results demonstrate that the adoption of FSMS 4.0 integrated with the three components (ecosystems, quality standards and robustness) significantly moderates the impact of the CSFs on achieving climate neutrality with lower inputs in human resources, infrastructure investment, integration and external assistance, and higher inputs in strengthening food safety administration.

This study provides empirical findings that fill the research gap in understanding the relationship between climate neutrality and the CSFs of sustainable FSMS while considering the moderating effects of the FSMS 4.0 components. The results provide theoretical and practical insights into how the food production sector can utilise IR 4.0 to attain sustainable FSMS for achieving climate neutrality.

Fresh vegetables contain advantageous phytochemical components, making them one of the most significant sources of nutrition. The threat of harmful bacteria still exists because these vegetables are not heated in restaurants before being consumed. Therefore, this study aimed to evaluate the microbial quality of fresh vegetables in restaurants of different levels.

A total of 499 fresh vegetable samples (from sandwiches and fresh-cut vegetable salads) were collected from 3 different types of food service establishment: 201 from international restaurants (IRs), 210 from national restaurants (NRs), and 88 from cafeterias (CAs). The samples were prepared and inoculated on specific growth media. The aerobic mesophilic bacteria (AMB) Campylobacter spp., Staphylococcus aureus (S. aureus), Enterobacteriaceae, Escherichia coli (E. coli) and yeast and molds were counted, and Listeria monocytogenes, Salmonella spp. and Escherichia coli O157 were detected using specialized medium.

High counts of S. aureus, above 3 log cfu/g, suggested that 71.5% of samples collected from NRs and 77.3% from CA were not accepted, whereas 81.6% of samples collected from IRs were accepted. The low population of E. coli, less than 2 log cfu/g, suggested that 99.0, 97 and 92.0 % of samples collected from IRs, NRs and CA, respectively, were accepted. Listeria monocytogenes and Escherichia coli O157 were absent from every sample. One sample was positive for Salmonella spp. in each of the NR and CA sample groups.

RIs adhere to health and hygiene standards better than NRs and CAs, according to the findings of vegetable contamination tests.

The purpose of this study is to understand the psychological mechanism that affects consumer trust by focusing on the formation and influence process of psychological contracts, and taking this opportunity, explore the influence paths of food quality, food safety and service quality on consumer trust in the online food market, and provide theoretical suggestions for building trust in food businesses' consumers.

This study is based on an empirical investigation and uses partial least square structural equation modeling for analysis. Survey data were collected online from 359 APP users of online food transaction platforms in China.

Food quality, food safety and service quality influence consumer trust through the mediating effects of relational and transactional psychological contracts. However, the differences between these influencing paths are obvious and shift with changes in the marketing channels.

This study contributes to the body of consumer trust research by exploring online food transactions as an emerging trend in China. Some optimization strategies for food quality, food safety and service quality are provided for enterprises involved in online food transactions.

This is a pioneering study revealing psychological contracts as a missing but significant mediator between consumer trust and its antecedents.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.