An Exploratory Study of Critical Issues and Variables Affecting the Food Supply Chain Risk Iceberg

The food supply chain ecosystem is critical, and a budding sector; this area has several challenges that shall be addressed and requires meticulous attention to detail and environment that are to be considered apart from the general issues that one entity experiences in a broad supply chain environment. It makes the Food Supply Chain Management a complex and precision-driven area towards quality and environmental factors to be dealt with recurrently. The critical aspects of the food supply chain are the cold chain, infrastructure, technology, knowledge, and post-harvest issues. These issues are analysed using statistical methods and interpretation to better understand food supply chain management.


Introduction
(Bautista et al., 2014) introduces us as food is the bedrock of life and the foundation of our physical, spiritual and emotional wellbeing, which is at the heart of many critical environmental, social and economic challenges we confront. Sustainability issues, climate changes, water scarcity, food security and sustainable nutrition, consumer attitude, demographic change, empowered producers, therapeutic approach, resilient value networks, sustainable market mechanisms, connected consumers are some of the challenges to name. To meet the globalised market demands, value chains are more complex, and this complexity carries with its opportunities for growth into new markets.

Methodology Problem Statement
Huge losses in the food supply chain due to critical factors/variables. Identification of key issues in the food supply chain to find an innovative solution.

Objectives
• To explore the key issues affecting the iceberg of the food supply chain.
• To analyse the supply chain performance and its relationship with the critical threats.

Literature Review
There is a gap among the existing methods in managing the fruits and vegetables food supply chain. Uncoordinated information from downstream to upstream of the supply chain has created a lot of wastages and losses for most food processors. The recall of expired products justifies it due to excessive supply. The inaccurate information suggests that the processors work on unreliable improved (bullwhip effect) demand data, with profound cost implications (Lee, 2004;Ouyang and Daganzo, 2008). For instance, a facility that processes the fruits and vegetables visited had a recalled product of about 10 tons of tomato sauce; this was a massive loss for the company to recover. (Minegish and Thiel, 2000) the company has to incur labour costs, transportation costs, destruction costs, primary and secondary raw materials etc. One of the respondents from the brewing industry reported incurring inventory costs of about 2 to 3 % of their value, i.e. From rental, interest foregone, obsolescence/damage/expire, insurance, handling, security and stock valuation.
The unfamiliarity of inventory at wholesalers' and retailers' stores had the following impacts on the processors.

Research Hypothesis
• H1: There is a significant direct negative relationship between Performance-related risks and supply chain performance • H2: There is a significant direct negative relationship between information and knowledge asymmetry related risks and supply chain performance • H3: There is a significant direct negative relationship between market-related risks and supply chain performance Micro-level Hypothesis for subfactors H1.1 There is a direct positive relationship of in-transit storage conditions with overall supply chain performance H1.2 There is a direct negative relationship of in-transit delays with overall supply chain performance H1.3 There is a direct positive relationship of supplier reliability with overall supply chain performance H1.4 There is a direct negative relationship of poor quality with overall supply chain performance H1.5 There is a direct negative relationship between inventory fluctuations with overall supply chain performance H1.6 There is a direct negative relationship of operations downtime due to process variability with overall supply chain performance H2.1 There is a direct negative relationship between IT failures with overall supply chain performance H2.2 There is a direct negative relationship of Data errors with overall supply chain performance H3.1 There is a direct negative relationship of Credit risk with overall supply chain performance H3.2 There is a direct negative relationship of Trade inflation with overall supply chain performance

Analysis
Industry Professional Survey: Survey done of key stakeholders (distributors, retailers, end customers, supply chain experts, industry operations managers) A qualitative thematic study was done with inputs on risks practically faced in the food supply chain from experienced 50 industry experts. The product of the two coded parameters is expressed to design a prioritising factor herein. During a focus group discussion in a panel, the industry experts debated the challenges and conflicts in prioritising and identifying these in the supply chain and tabled the issues.

Risk or Threat factors identified
The table collates data through thematic study, industry experts, and literature review.  The Table highlights the critical issues based on the occurrences in the literature and information in the secondary sources, industry experts and field inputs. The majority of the respondents agreed that the organisation faces the following supply chain management risks: Information and Knowledge Risks are more prominent in the organisation 98%; Performance related Risks are common in the organisation 92%. Market Risks are more prevalent in the organisation 74%. There seems to be a need to further analyse with primary data to precipitate and prioritise all conflicting issues in the present context of the disruption-prone food supply chain.

Cronbach Alpha
The Cronbach's Alpha Test assesses the reliability or the internal consistency of all the test items. An alpha value greater than 0.70 indicates higher acceptable internal consistency. From the tests, it is understood that Performance Risks (alpha value -0.905), Information and Knowledge Risks (alpha value -0.801), and Market risks (alpha value -0.886) imply that all their independent variables are closely related, respectively.

Factor Analysis
The tested sampling adequacy shows that the value of KMO to 0.775 (EFA-1) and 0.763(EFA-2), which is greater than 0.5. All the variables are accepted and can be taken forward for Confirmatory Analysis.

Confirmatory Factor Analysis (with field data) for Finalised Variables Path Diagram
The path diagram is considered for the initial input for the confirmatory factor analysis. The information is obtained from the data set prepared post data collection from the field study. Initial regression weights are allocated to non-observed variables. The variables considered for the confirmatory factor analysis have been considered for further research. The primary independent variables are network management, operational indicators and legal aspects which affect the performance of the non-fragmented food supply chain.  Source: Computed from the data analysed from the Field Survey Tablele 6 represents the output of the ANOVA analysis and shows the significant relationship between dependent and independent variables. The factors post the EFA1 EFA2 CFA. The funnelled variables are shown to be substantial since the p-value is less than 0.05. Source: Computed from the data analysed from the Field Survey Table 7 reveals the Food Supply Chain Management Performance Regression Analysis with various key impact factors. A regression result is given as R-Square = 0.767, F-Value = 50.76 and significance (P-Value <0.045) showing the positive significance relationship.

Discussion Solution
Several models and frameworks can be designed to address these variables and predict the risks. The applicability of the model framework would provide a sound approach to (i) identify the key variable and the related consequences that affect the food supply chain (ii) measure the performance of the supply chain and its relationship with the variables (iii) mitigating the risks by scheduling and strategizing (iv) monitor the different types of risks in the food supply chain system.
A risk iceberg approach is suggested so that seen and unseen variables can be analysed by the stakeholders. It is an essential framework to identify variables and work on the various techniques to look for easily 'Seen Risks' (visible and easily visible) versus the hidden 'Unseen Risks' (need to be discovered and identified through analysis) that erupt any disruption. Organisations' managers can create a framework for better understanding operational risks and responding to and recovering from operational disruptions. Safeguard business by knowing the potential hidden risks.

Conclusion
This paper dealt with secondary and primary research contributing to the risk factors affecting the food supply chain system. The critical issues of the food supply chain risks are performance threats: storage conditions, forecasting errors, poor quality, price fluctuations, operations downtime, delay, and inefficiencies. Managers need to look at all the aspects of threats and how well the issues are addressed in their ongoing strategy. The model framework helps managers identify the iceberg risks and handle disruptions.