The massive rise of Big Data generated from smartphones, social media, Internet of Things (IoT), and multimedia, has produced an overwhelming flow of data in either structured or unstructured format. Big Data technologies are being developed and implemented in the food supply chain that gather and analyse these data. Such technologies demand new approaches in data collection, storage, processing and knowledge extraction. In this article, an overview of the recent developments in Big Data applications in food safety are presented. This review shows that the use of Big Data in food safety remains in its infancy but it is influencing the entire food supply chain. Big Data analysis is used to provide predictive insights in several steps in the food supply chain, support supply chain actors in taking real time decisions, and design the monitoring and sampling strategies. Lastly, the main research challenges that require research efforts are introduced.

Big Data in food safety- A review

Research background: The difference of war and peace can help gain an under-standing of the differences in the management of a company's reputation in terms of its stability as compared to the state of a reputation crisis. The question of practical confirmation, which is left open, is whether there is a positive correlation between the anti-crisis activity of the reputation management system and its stability in a long-term perspective, or whether these two factors are inversely related.
Purpose of the article: This research is essentially aimed at studying the impact of innovation activity, media activity, and corporate social responsibility on reputational stability as well as on anti-crisis reputational sustainability.
Methods: Indicators of innovation activity, media activity, corporate social responsibility, reputational stability, and anti-crisis reputational sustainability were collected in a sample of the most frequently mentioned in the media leading companies of the Ukrainian economy (N = 315), using an online survey done among 110 industry experts within the framework of the Reputation ACTIVists All-Ukrainian Ranking of Corporate Reputation Management Quality over February-March'2019 period. Structural equation modeling (SEM) in using the maximum likelihood estimation method was applied to examine the associations between above-mentioned indicators, according to the aim of the study.
Findings & Value added: The results of our study revealed: 1) the existence of a significant correlation between CSR and reputational stability; 2) innovative and media activity are the most significant variables to provide anti-crisis sustainability; 3) CSR is less important for ensuring anti-crisis sustainability than for maintaining reputational stability; 4) anti-crisis sustainability is significantly more dependent on media activity than reputational stability is. By better understanding the roles of innovation activity, media activity,  and corporate social responsibility, the company?s management in Ukraine can leverage the results of the study to improve reputation management performance, differentiating approaches in circumstances of a crisis and stability.

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Reputation stability vs anti-crisis sustainability: under what circumstances will innovations, media activities and CSR be in higher demand?

Online Social Networks (OSNs) are an integral part of the modern lifestyle, and the use of OSN is highly prevalent today. OSNs have enabled the generation of unprecedented quantities of data on users, their interests, relationships, actions, opinions, locations visited, items purchased, and their experiences in various aspects of life. Data and information related to reputation and influence exist on OSNs and are hidden. The objective of this study is to provide a better and deeper understanding and a detailed review of the current state of research pertaining to the measurement of reputation and influence in OSNs, specifically Twitter. We conducted a Systematic Literature Review to collect, analyze, and synthesize data on the accuracy and value of previous literature that has focused on this field, has addressed a variety of topics, and has been published in digital databases between 2010 and September 2019. We followed a predefined review procedure that integrated both automatic and manual search strategies to cover all relevant research papers published in this period.

/pdf/measuring-reputation-and-influence-in-online-social-networks-2bs2067kub.pdf

Measuring Reputation and Influence in Online Social Networks: A Systematic Literature Review

Examining organization-public relationships in crises: A thematic meta-analysis of updated literature from 1997 to 2019

To date, many firms tend to use corporate social responsibility (CSR) communication and marketing as a means to offset their irresponsible behaviors and unscrupulous business practices. Often time, they can easily get away with this in the context where the institutional settings are weak, and corporate social irresponsibility (CSIR) and corruption are widespread. The purpose of this study is to explore stakeholders’ attribution concerning CSR claims of four beverage manufacturing companies operating in America’s poorest country (Haiti) where CSIR and corruption remain widespread. This study also explores whether there are differences in demographic characteristics (e.g. gender, corporate affiliation and education) regarding stakeholders’ attribution of CSR claims of these companies.,Given the exploratory nature of this study, an inductive research approach (qualitative plus quantitative) and supported by an interpretive approach were used.,The overall results of this study show that internal (employees) and external stakeholders alike consider the CSR claims of these companies as “cosmetic,” with no significant difference in their affiliation. The results also show no significant differences in the age groups but significant differences in gender and level of education regarding stakeholders’ attribution of firms’ CSR claims.,By addressing firms’ CSR claims from the perspectives of internal and external stakeholders through means of a mixed methods approach, this study adds an important contribution to the relevant literature.

Authentic or cosmetic: stakeholders’ attribution of firms’ corporate social responsibility claims

The purpose of this paper is to investigate the evolution of online sentiments toward a company (i.e. Chipotle) during a crisis, and the effects of corporate apology on those sentiments.,Using a very large data set of tweets (i.e. over 2.6m) about Company A’s food poisoning case (2015–2016). This case was selected because it is widely known, drew attention from various stakeholders and had many dynamics (e.g. multiple outbreaks, and across different locations). This study employed a supervised machine learning approach. Its sentiment polarity classification and relevance classification consisted of five steps: sampling, labeling, tokenization, augmentation of semantic representation, and the training of supervised classifiers for relevance and sentiment prediction.,The findings show that: the overall sentiment of tweets specific to the crisis was neutral; promotions and marketing communication may not be effective in converting negative sentiments to positive sentiments; a corporate crisis drew public attention and sparked public discussion on social media; while corporate apologies had a positive effect on sentiments, the effect did not last long, as the apologies did not remove public concerns about food safety; and some Twitter users exerted a significant influence on online sentiments through their popular tweets, which were heavily retweeted among Twitter users.,Even with multiple training sessions and the use of a voting procedure (i.e. when there was a discrepancy in the coding of a tweet), there were some tweets that could not be accurately coded for sentiment. Aspect-based sentiment analysis and deep learning algorithms can be used to address this limitation in future research. This analysis of the impact of Chipotle’s apologies on sentiment did not test for a direct relationship. Future research could use manual coding to include only specific responses to the corporate apology. There was a delay between the time social media users received the news and the time they responded to it. Time delay poses a challenge to the sentiment analysis of Twitter data, as it is difficult to interpret which peak corresponds with which incident/s. This study focused solely on Twitter, which is just one of several social media sites that had content about the crisis.,First, companies should use social media as official corporate news channels and frequently update them with any developments about the crisis, and use them proactively. Second, companies in crisis should refrain from marketing efforts. Instead, they should focus on resolving the issue at hand and not attempt to regain a favorable relationship with stakeholders right away. Third, companies can leverage video, images and humor, as well as individuals with large online social networks to increase the reach and diffusion of their messages.,This study is among the first to empirically investigate the dynamics of corporate reputation as it evolves during a crisis as well as the effects of corporate apology on online sentiments. It is also one of the few studies that employs sentiment analysis using a supervised machine learning method in the area of corporate reputation and communication management. In addition, it offers valuable insights to both researchers and practitioners who wish to utilize big data to understand the online perceptions and behaviors of stakeholders during a corporate crisis.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=7493&context=lkcsb_research

Jie Sheng Chua

Papers

Evolution of corporate reputation during an evolving controversy