Applications of information and communication technology for sustainable growth of SMEs in India food industry

Resources, Conservation & Recycling 147 (2019) 10–18

Contents lists available at ScienceDirect

Resources, Conservation & Recycling journal homepage: www.elsevier.com/locate/resconrec

Full length article

Applications of information and communication technology for sustainable growth of SMEs in India food industry

T

⁎

Rajesh Kr. Singha, Sunil Luthrab, Sachin Kumar Manglac, , Surbhi Uniyald a

Management Development Institute, Gurgaon, Haryana-122007, India Department of Mechanical Engineering, State Institute of Engineering & Technology (also known as Government Engineering College), Nilokheri, India c Knowledge Management & Business Decision Making Plymouth Business School, University of Plymouth, Plymouth, United Kingdom, PL48AA d Department of Mechanical Engineering Graphic Era University, Dehradun-248002, Uttarakhand, India b

A R T I C LE I N FO

A B S T R A C T

Keywords: Food supply chain Information communication technology Resource management Indian small and medium enterprises Sustainable growth Grey based Decision-making trial and evaluation laboratory

Indian food sector is facing severe problem of wastage of about 30% of farm products due to inefficiency in operations of Small and Medium Enterprises (SMEs). The SMEs in Indian food sector are facing different challenges, such as financial issues, lack of technical skills and investment in the business etc. In this sense, several key factors can help food SMEs in reducing wastage of farm products and lowering energy consumption for sustainable growth. Thus, this paper tries to identify and analyse key factors for Information Communication Technology (ICT) applications for a sustainable growth of SMEs in Indian food sector. Grey based DecisionMaking Trial and Evaluation Laboratory technique was applied for analysis of factors. From findings, ‘Government initiatives and policies’, ‘Public-private partnership’, and ‘Encouragement to ICT service provider’ are topmost influential cause group factors. While, ‘ICT integrated effective food supply chain’, ‘Coordination between different departments’, and ‘Collaboration and strategic alliances across supply chain’ are highest influenced factors. Results suggests that ‘Government policies and initiatives’ are at the core of the efforts to upgrade food supply chain. As, Indian government is the largest customer of SMEs and controls various policymaking aspects in food sector. Therefore, government has to take steps to encourage private and foreign investments as well as promote IT service providers and business environment related economic policies to improve competitiveness of Indian food sector. This work would help managers to develop efficient ICT applications for an effective sustainable growth of SMEs in their respective food supply chains.

1. Introduction The food industry plays very important role in economic growth of a country. It helps in ensuring food requirements of people and employment creation (FAO, 2017; Sharma et al., 2019). With increasing population, this sector is facing tremendous challenges such as growing demand of food, environmental protection, increasing wastage and poor food quality (Bonneau and Copigneaux, 2017). Food supply chains explain the process of how food reaches from farm to fork by involving several functions, including production, processing, distribution, consumption and disposal (Faisal and Talib, 2016; Mangla et al., 2018). In response, organisations in food sector are trying to implement Information Communication Technologies (ICT), to re-structure their value chain activities to reduce wastage (Hendricks et al., 2007; Ahumada and Villalobos, 2009; Dora et al., 2016). ICT applications assist organisations to develop an efficient information sharing system

to achieve better utilisation of resources and environmental protection (Sambamurthy et al., 2003; Thakkar et al., 2013; Mishra et al., 2017). India is among largest producers in agri-food business (WTO, 2004). However, Brazil, Thailand and Argentina have emerged as major exporters in addition to India and China. In India, the wastage of agricultural produce is sizeable (approximately 40%–50% wastage in vegetables and fruits, 35% in milk, 21% in meat etc.). The processing of agriculture produce in India are extremely low (only 20%) and wastage is anticipated to be valued at approximately 8.5 billion US$ (D and B Report, 2015). In India, small and medium enterprises (SMEs) constitutes major part of business and approximately 95% Industrial units in India are under SMEs category with merely 6.29% contribution to GDP (Singh et al., 2008). Singh et al. (2008) stated that Indian SMEs are reluctant in applying ICT tools across their functions in supply chain due to various internal and external constraints. SMEs comparatively operate with lower resources and facilities, that seeks to expand in

⁎

Corresponding author. E-mail addresses: [email protected] (R.K. Singh), [email protected] (S. Luthra), [email protected], [email protected] (S.K. Mangla), [email protected] (S. Uniyal). https://doi.org/10.1016/j.resconrec.2019.04.014 Received 22 January 2019; Received in revised form 9 April 2019; Accepted 9 April 2019 0921-3449/ © 2019 Elsevier B.V. All rights reserved.

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

management. Therefore, it is time for Indian food SMEs to integrate their supply chains by ICT applications for their sustainable growth. Current research on ICT focuses technological advancements and innovation; however, an integration of ICT in food supply chain is nascent in literature (Narula, 2017; Zhong et al., 2017; Luthra et al., 2018a). Therefore, need arises to uncover key factors for ICT applications in Indian SMEs specifically from food industry for sustainable growth of their supply chains. Under such circumstances, the present research seeks in attaining the following objectives, stated as:

terms of their supply chain capabilities (Jayaram et al., 2014). Bhagwat and Sharma (2007) observed that SMEs lag in terms of ICT applications as compared to larger firms. As for as food industry context, the application of ICT in SMEs of food industry is a major concern. Managers’ needs to design an efficient supply chain planning system to provide high quality and safer food to consumers while meeting sustainability requirements (Shirani and Demichela, 2015; Verdouw et al., 2016; Dania et al., 2018; Luthra et al., 2018a). For ensuring sustainable growth, SMEs in food industry need to operate in national and international markets. Bhandari et al. (2019) have observed that for sustainable growth, selection of technologies to ensure cleaner production is very important.Song and Wang (2017) observed that organisations should participate in global chain and improve their production efficiency. Greater competition in global markets requires that SMEs should be more innovation oriented to improve efficiency of supply chains (Bernard et al., 2007; Filipescu et al., 2009; Karipidis et al., 2009). Traceability of food products is important requirement for making supply chain more efficient (Hobbs et al., 2005; Li et al., 2006). For exporting in developed countries, traceability of product is one of the mandatory requirements. The traceability means that the required information about food products be shared across all nodal points of a supply chain in standard language (Regattieri et al., 2007; Fritz and Schiefer, 2009). In recent past, traceability has been integrated as a mandatory regulation in food sector in many nations (Riviere and Buckley, 2012). Government of India has also started many initiatives to ensure traceability in food sector such as end-to-end computerisation of public distribution system, direct cash and subsidy transfer to farmers account etc. India is yet to follow this path completely (Schroeder and Tonsor, 2012; Dandage et al., 2017a, 2017b). Current traceability systems are not able to ensure effective linkage of food chains records, accuracy and timely sharing of data (Badia-Melis et al., 2015). Stefansson and Tilanus (2001) observed that tracking and tracing system must be connected with information systems. Effective application of ICTs will contribute significantly in improving traceability across supply chains. According to Song and Wang (2018), application of technologies can help organisations in creating sustainable competitive advantage. In addition, ICT can complement the logistics and supply chain efficiency in the food industry (Mohezar and Nor, 2014; Pramatari, 2015; Akhtar et al., 2016). It is ultimately going to help SMEs for sustainable resource management (Tseng et al., 2017; Gong et al., 2018).

i To identify key factors for ICT applications for sustainable growth in Indian SMEs from food sector; ii To organise factors into cause and effect groups to promote ICT applications for sustainable growth in SMEs. This work seeks to identify and analyse various key factors that contribute the use of ICT applications for sustainable growth in the Indian SMEs by taking food supply chain perspective. Keeping in view the first objective, a comprehensive literature survey is performed. This study utilises the Grey based Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. Grey based DEMATEL technique assists in organising the causal relationships between factors in an uncertain and complex environment (Luthra et al., 2017) under vague and imprecise information. Fuzzy DEMATEL can be used in place of Grey based DEMATEL, but it lacks in the mapping of a membership function from a managerial context (Luthra et al., 2018b). The foremost contributions of this work are given as follows:

• This study aims to distinguish various key factors that contribute to •

the use of ICT applications for green growth in the Indian food SMEs perspective. This research would assists in generating higher environmental performance and sustainable development in a nation like India. This work further evaluates the causal relationships among ICT based factors in food SMEs perspective. For this, the present work applied Grey-DEMATEL as a methodological contribution and hence developed a causal model of factors.

In total, this paper is divided into 6 Sections, which are discussed one-by-one in below provided text. 2. Literature review

1.1. Problem description and objectives of the research This section provides relevant literature on status of ICT applications in SMEs of food sector in global and Indian scenario.

In India, agriculture is a major source of employment. India has also been registered as a global producer in world food’s market, yet the productivity levels are not highly significant (National Manufacturing Competitiveness Council, 2012). This is due to inadequacy in understanding and interpretation of factors such as lack of skilled work force, use of obsolete technologies, governance issues etc. (FICCI, 2010; Rais et al., 2014). Notably, over 98% of food is sold in unorganised markets in India (Brand Equity, 2016). Due to dominance of unorganised operations, most of the SMEs are not well integrated with supply chain (Singh, 2014). This leads to significant food wastage and results in reduced productivity. For an instance, a loss of more than 6.7 billion US $ is noted annually in fruits and vegetables because of lack of management and integration among stakeholders (Balaji and Arshinder, 2016). It is evident how little importance is given to ICT applications among Indian food SMEs causing inefficiencies in the way they function (Verdouw et al., 2016; Dandage et al., 2017a, 2017b). The usage of ICT can enhance business efficiency by making an optimal use of resources, decreasing waste and power consumption, and provides a way to attain sustainable growth opportunities from managerial viewpoints (Song and Wang, 2018). Bamfo et al. (2019) have also observed that ICT applications can improve sustainability of supply chain processes such as procurement and inventory

2.1. ICT applications in SMEs of food sector: global and indian scenario Information sharing in the agri-food supply chain is complicated due to involvement of multiple actors such as farmers, producers, distributors etc. The possible reasons could be uncertainty of consumer demand and availability of resources etc. (Kumar and Nigmatullin, 2011; Govindan, 2018). Industrial production of food requires numerous product alterations and processing steps to vary the food composition. If, these alterations and processing steps are not cautiously monitored then can disturb the food quality etc. (Thakur et al., 2011; Kotsanopoulos and Arvanitoyannis, 2017). Therefore, proper information sharing between agri-food supply chain actors is required to deliver differentiated information to meet up the demand (Trienekens et al., 2012). In recent years, augmented competition and the advancement in ICT have changed business scenario of agri-food supply chains predominantly in the European Union (EU), which is mainly characterised by the proliferation of SMEs (Mangina and Vlachos, 2005; Ghadge et al., 2017). The Indian food market is envisaged at over US$ 182 Billion. Further, the retail food sector in India is expected to rise US$ 175 11

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

In this sense, the combined grey-DEMATEL technique is used (Bai and Sarkis, 2013; Su et al., 2016) in this work. Following steps are undertaken to implement Grey-DEMATEL (Shao et al., 2016):

Billion to US$ 400 Billion by 2025. The business environment of Indian SMEs needs to be studied to understand why it is so unorganised (NRAI, 2013) and not working properly like Chinese SMEs. Ritchie and Brindley (2000) quoted in their research that most of SMEs are using internet and ICT tools for advertising rather than managing their operations and supply chain functions. Sahay et al. (2006) reported that the budget for ICT applications in Indian SMEs is quite low even less than 0.1% to 3–5 % of their gross sales i.e. ineffective use of ICT applications in Indian SMEs is leading wastage of materials, poor optimisation of resources, poor management of SC activities etc. This study also identifies several research gaps such as poor SCM applications in SMEs, Lack of integration, Lack of understanding between alliances, Immature buyer-supplier relationships, Nonexistence of performance measurement systems, Poor supply chain framework, Poor use of IT tools and Poor strategic vision. Due to this, it has become quite challenging for SMEs to compete in the global world. Vaaland and Heide (2007) surveyed 200 Norwegian companies taking into consideration the preparedness of SMEs. The findings of the survey were not much positive, as it showed that SMEs are not giving enough attention to planning and control methods, compared to their larger counterparts, and that is why Indian SMEs were kept in comparatively lower competitive position.

i Recognition of decision elements, i.e. key factors for ICT applications for sustainable growth in Indian food SMEs. The decision elements are identified by literature review and expert’s inputs. ii Formation and computing the overall grey-direct-relation matrix between factors. For this, experts are asked to provide their feedback for rating the strength of relations between any two factors based on the scale given Table 2. Their responses are written in Matrix A (m × m), where m is the number of factors. iii Normalise the grey number on the lower bound using the following expressions, giving ‘n’ number of experts. max ⊗x ijn = (⊗x ijn − min ⊗x ijn ) Δmin max ⊗x ijn = (⊗x ijn − min ⊗x ijn ) Δmin

Among them, max Δmin

= max ⊗x ijn − min ⊗x ijn

(1)

iv Transform the grey number into total normalized crisp value using Eq. (2):

2.2. Key factors to ICT applications for sustainable growth in SMEs of food sector

Yijn = To identify key factors for promoting ICT applications in Indian SMEs in their food supply chains, a literature survey was performed. Thus, a literature review was made using key words search e.g. Key Factors/Enablers/Success Factors/Drivers + ICT applications + food supply chain + Small and Medium Enterprises and or India etc. The relevant articles and reports were then downloaded, reviewed and analysed. In this way, seventeen important key factors to ICT applications in food supply chain were identified in through extensive literature support. Further, to validate the recognised factors, sixteen experts from various SMEs associated with Indian food industry were contacted. Only five industrial experts out of the sixteen experts and five academicians out of twelve decided to provide their response. Hence, total ten experts were selected, with two supply chain professionals, two IT experts, one production manager, three professors from operations and decisions, and two professors from information systems. The selected experts are extremely experienced in their areas and are capable in decision-making. In this study, the finalisation of identified factors for ICT applications in food SMEs was accomplished by discussion with decision team. Thus, the identified factors have been described in Table 1.

⊗_x ijn (1 − x ijn ) + ⊗−x ijn ∗ ⊗ −x ijn 1 − ⊗_x ijn + ⊗−x ijn

(2)

v Further, the final crisp values are computed using Eq. (3): max Zijn = min ⊗ x ijn + Yijn Δmin j

(3)

vi Define number weight for experts. vii Next, a normalized matrix is obtained through Eqs. (4–5): D = A×S

Where , S =

(4)

1 , i, j = 1, 2, 3.......n n max ∑ j = 1 ⊗aij

1≤i≤n

(5)

Next, we obtain the total relation matrix (T) through Eq. (6): T= D (I-D)−1

(6)

viii. Compute the causal variables for the recognised factors: The summation of row (Ri) and column (Cj) are computed by using Eqs. (7) and (8). n

⎡ ⎤ Ri = ⎢∑ tij ⎥ = i 1 ⎣ ⎦n × 1

3. Research methodology

(7)

n

⎡ ⎤ Cj = ⎢∑ tij ⎥ i = 1 ⎣ ⎦1 × n

This work is based on grey-DEMATEL methodology. Prof. Deng has introduced the grey theory in 1982. DEMATEL assists in evaluating the complicated decision issues by revealing the strength of relations between elements. DEMATEL can illustrate the relationships between elements using graphical representation and cause and effect groups (Gabus and Fontela, 1972). Kumar and Dixit (2018) have used DEMATEL approach for evaluating critical barriers for managing waste of electrical and electronic equipment (WEEE). Compared to DEMATEL, researchers may use interpretive structural modelling (ISM) and analytical hierarchy process (AHP) approach but these techniques do not provide cause and effect relations between the factors (Mangla et al., 2015, 2016; Luthra et al., 2017; Thakur and Mangla, 2019). The grey set theory can solve the uncertain problems caused by vagueness and inaccurate information (Rajesh and Ravi, 2015) and improve the accuracy of human decisions (Xia et al., 2015) even with the smaller sample size (Hsu et al., 2013).

(8)

Where, tij represents elements in total relation matrix. iv. Next, a cause-effect diagram of the key factors is obtained using Eqs. (9) and (10). Pi = {Ri + Cj |i = j} Ei = {Ri -Cj |i = j}

(9) (10)

Where, prominence (Pi) and net effect (Ei) For the purpose of DEMATEL calculations, the coding was made in the Excel sheet. All the calculations have been made by especially designed Excel sheet. Further, we draw a research framework for this work (shown in Fig. 1). This framework organise the ICT enabling factors to SMEs in food sector, through Grey-DEMATEL methods. In the first phase, the 12

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

Table 1 Key factors to ICT applications for sustainable growth in Indian food SMEs. Key factors to ICT applications

Brief description

References

Government initiatives and policies (F1)

Government is the central entity in food security of nation. Government supportive policies can help in enabling open market conditions, training and practical support to farmers, encouraging cooperatives, rural property clarification, assistance in risk management, investing in infrastructural development. There is the need to strengthen public-private partnership through different channels. Government needs to in still faith in the private sector to invest in food sector’s modernisation. Developing integration within supply chain partners is necessary for business organisations. Despite India’s excellence in IT, this specialised service industry is unable to cater home demand, and support the critical sector SMEs like that of Food Supply Chain. Further, government’ adoption of ICT applications in procurement, logistics etc. will not only encourage the SMEs but will also act as boost to ICT service providers. The efficient use of ICT Service Providers can result into cost reduction for carrying out various transactions within a business organisation. With innovation in technology such as cloud computing, ICT service companies need to design innovative business models to make it affordable for all SMEs. Food sector typically is one where in demand and supply are dependent on season, so it makes less sense to the SMEs to invest in ICT infrastructure that is not required all round the year. However, if SMEs are offered services on the lines of “pay-as-you-go”, they would certainly open up. As the human resource of food sector’s SMEs is not well prepared for ICT systems, the additional challenges of handling complex and unsafe systems will never let the implementation be successful. Together the SMEs will have synergistic impact by being able to bring sustainability in their businesses. Coordinating among various activities is important in the success of food industry. The food supply chain frequently faces the shock from climatic conditions, and thereby it is required that other shocks such as financial, policy-related etc. to this supply chain be minimised. Trust among partners is significant for longterm stability of a business organisation. The shocks need to be minimised, and set of cooperatives and other government initiatives will bring about the certainty in the food safety and quality. The increased collaboration and strategic alliances between growing entities will make ICT applications and systems reach more players at SME levels, which would improve their overall supply chain performance. With recent opening up of FDI, government has taken a step for pushing investments in logistics and storage facilities across food sector. This initiative will show its results in coming years for improving the competitiveness of food sector. Expanding foreign market is a significant factor for improving the performance of food industry. ICT enabled food supply chain can be developed only when each player contributes its bit by investing in ICT infrastructure within its premises. The above factors directly or indirectly would contribute in making up the management minds to invest in ICT infrastructure after evaluating its worth for their business. Human resources are key to food industry growth. HR skills and adequate training is crucial in improving the performance and reducing food wastage. In the present scenario, organisations need to derive value from its IT systems, rather than spending on it with not much useful work being done through it. The implementation of ICT would derive organisation for an improved change – deliver higher quality food at lower price. A technology-oriented organisation will absorb and keep pace with frequently changing technology and be able to handle the integration and change management with little glitches. Standalone ICT applications fail to bring out synergies from the investments made. The coordination of enterprise solutions is important, and hence results in performance improvement in a food supply chain. The management and the influencers in the agro sector SMEs need to be convinced about business benefits of ICT applications. SMEs need to be enlightened about formal investing techniques through banks and financial institutions, so that they are in position to evaluate their options, compare costs with benefits and take informed decisions. ICT applications such as traceability and virtualisation may help to tracking of different functions across food supply chains.

Kurnia et al. (2015); Aggarwal and Srivastava (2016); Sharma et al. (2019)

Public-private partnership (F2)

Encouragement to ICT service provider (F3)

Low cost service model (F4)

Simple and secured ICT applications (F5) Improved coordination between government and SMEs (F6) Stability in business environment (F7)

Revenue certainty (F8)

Collaboration and strategic alliances across supply chain (F9) Private and foreign investment (F10)

Investment in ICT infrastructure (F11)

HR recruitment and training (F12) Organisational change/Re-engineering (F13)

Smooth integration and change management (F14) Coordination between different departments (F15) Encouragement and intention for ICT application (F16)

ICT integrated effective food supply chain (F17)

Flynn et al. (2010); Chen et al. (2015)

Pramatari (2007); Singh et al. (2009); Tatoglu et al. (2016)

Thakkar et al. (2009); Kumar et al. (2013)

Gaukler (2010); Saguy and Sirotinskaya (2014); Vlachos (2014) Kumar et al. (2014); Akhtar and Khan (2015); Luo et al. (2018) Barratt (2004); Ngai et al. (2008); O’Reilly et al. (2015)

Kritchanchai (2004); Vlachos (2015)

Mohezar and Nor (2014); Akhtar and Khan (2015); Dania et al. (2018); Raut et al. (2019) Vickery et al. (2003); Kumar et al. (2013); Saguy and Sirotinskaya (2014); Pan et al. (2018)

Bhatt et al. (2010); Saguy and Sirotinskaya (2014); Tatoglu et al. (2016); Song et al. (2018); Bamfo et al. (2019)

Manning and Baines (2004); Mathur et al. (2012) Gunasekaran and Ngai, (2008); Tatoglu et al. (2016); Jakhar et al. (2018)

Dora and Gellynck (2015); Dora et al. (2016)

Chang et al. (2013); Dora et al. (2016)

Dyerson et al. (2009); Bhaskaran (2013); Dora et al. (2016)

Bhaskaran (2013); Aung and Chang (2014); Verdouw et al., 2016)

4. Data analysis and results

literature survey and expert inputs were used to identify and validate the important factors. Lastly, in phase 2, we analysed the factors for determining their cause and effect relations.

In this study, data analysis has been made in two phases. First phase is on validation of factors and second phase on evaluation of causal relationship for identified factors by Grey DEMATEL approach. 13

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

5. Discussions

Table 2 The grey linguistic scale for experts' assessments. (Source: Cui et al., 2018). Linguistic terms

Associated grey numbers

Values

No influence Very low influence Low influence High influence Very high influence

(0,0) (0,0.25) (0.25,0.5) (0.5,0.75) (0.75,1)

1 2 3 4 5

In India, there is a huge potential for growth of food sector SMEs but at the same time, there are number of reasons for lagging behind. Lack of knowledge and unenthusiastic attitude towards ICT adoption are the major reasons among them (Maurya et al., 2015; Dandage et al., 2017a, 2017b). Therefore, this research uncovered the factors affecting ICT applications for sustainable growth of SMEs in Indian food sector. From Grey DEMATEL analysis, it is observed that ten factors i.e. Government initiatives and policies (F1); Public-private partnership (F2); Encouragement to ICT service provider (F3); Low cost service model (F4); Improved coordination between government and SMEs (F6); Simple and secured ICT applications (F5); Stability in business environment (F7); Private and foreign investment (F10); Investment in ICT infrastructure (F11) and Revenue certainty (F8) are cause group factors. The cause group factors may be understood as independent factors and having a high impact on the system. Thus, organisation needs to focus on these factors as the root cause of all the other factors. ‘Government initiatives and policies (F1)’ factor has been found highest driving power and low dependence. Kumar et al. (2013) have stated that Government initiatives and policies are crucial to ICT applications for sustainable growth in Indian food SMEs. ICT applications will help to modernisation (RFID, Traceability and Virtualisation etc.) and innovativeness in food chain activities. This would further reduce wastage of farm products in India, and enhance competitiveness of Indian food supply SMEs. The research of Luthra and Mangla (2018) also reported that ICT applications would reduce process wastage to support green growth of Indian industries, which could not possible without the government initiatives and supported policies. This factor also has the topmost (E) score of 1.767, which means F1 is highly powerful factor. Food wastage has become a major concern in food value chains, so governments are seeking to response this issue to ensure secure food for society (Halloran et al., 2014). It means that government initiatives and policies are crucial to adopt ICT applications in Indian food SMEs in their supply chain context to reduce food waste. ‘Public-private partnership (F2)’ comes next to F1. Public-private partnership is required to reform the agri-food sector for sustainable resource management. Governments may prioritise attracting foreign as well private investment and to channelize these funds in holistic development of agri-food sector (Rueda et al., 2017). ‘Encouragement to ICT service provider (F3)’, comes next based on its (E) score. Next, is ‘Low cost service model (F4)’, which could be validated from the research of Mohezar and Nor (2014) that suggested that ICT adoption in food businesses can affect a business organisation’s capability to innovate and could generate more economic benefits. From (E) score,

Fig. 1. Proposed research framework.

4.1. Phase 1: validation of the factors Based upon expert’s feedback, all identified literature based factors were validated (as details are provided in subsection 2.2).

4.2. Phase 2: evaluation of causal relations of the Factors The listed factors were evaluated for pair-wise comparisons and experts responses were recorded using a scale given in Table 2. Taking an average of expert’s responses, an average grey-direct relation matrix for factors was formed and shown in Table 3. After this, datasets Prominence (Pi) and Net effect (Ei) datasets for factors are determined (see Table 5). Then, the cause and effect diagram for the factors is constructed as presented in Fig. 2.

Table 3 Average direct relation matrix of factors to ICT applications for sustainable growth in Indian food SMEs. Factors

F1

F2

F3

F4

F5

F6

F7

F8

F9

F10

F11

F12

F13

F14

F15

F16

F17

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17

0 1.33 1 1.33 1 1.33 1.33 1.67 2 1.33 2.33 3 2 1 1.67 0.67 2

3 0 2 1.33 2 1 1.33 1.33 1.33 1.67 1.33 1.67 1.67 2 1 2 2

3 3 0 1.33 2 1.67 1.67 1.67 2 1.67 1.33 1.33 1 1.33 1 1.67 2

3 3 3 0 1.67 2 2 1.33 1.67 1.33 1.33 1.33 1.67 1.33 1.67 1.67 1

2.67 3 3 3 0 2.33 2.33 1.33 1.67 1.33 2 1.33 1.67 1 1.33 1.67 1

3 3 2.67 2.67 2 0 1.67 1.67 1 2 2 1.33 1 1.33 1 1.67 2

3 2.67 2.67 2.67 2 3 0 1 1.33 2 1.67 2.33 1.33 1.67 1.33 1.67 1

2.67 3 3 2.67 3 2.67 2 0 1.33 1.67 2.33 1.33 1 1.67 1 1.33 3

2 2.33 2.67 3 3 2.67 2 2.67 0 2.67 2.33 2.33 2.67 2.33 2.33 2.33 1.67

1.67 2 2.33 2.33 2.67 2.67 3 2.33 1.33 0 2.33 2 1.67 1.67 1 2.33 1

2 1.67 2.33 2 2.67 2.33 2.67 3 1.67 2.67 0 0.33 1.67 1.67 1.67 2.67 1.33

1.67 1.67 2 2 2 2.33 2.67 2.67 1.33 2.33 2.33 0 2 2.33 1.67 2.67 2

2.67 2.33 3 2 2.33 2.67 2.33 2.67 1 2.67 2.33 2.67 0 2 2 2.33 1.67

2 2.33 2.33 2 3 2 2.33 3 1 2.67 2.67 4 2.33 0 1.67 3 1.67

2.67 2.67 2 2.33 2.67 3 3 3 1.33 2.67 2 2.33 2.33 1.67 0 3 1.33

2 2 2.33 2.33 2 2 2 2.33 1.67 2.67 2.67 2.33 2 4 1.33 0 1.33

2.67 3 2.67 3 2.33 2.67 3 3 2 3 3 1.67 1.33 1.67 2.67 2.67 0

Next, it is normalized direct-relation matrix, which is further transformed into total direct relation matrix as presented in Table 4. 14

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

Table 4 Total direct relation matrix of factors to ICT applications for sustainable growth in Indian food SMEs. Factors

F1

F2

F3

F4

F5

F6

F7

F8

F9

F10

F11

F12

F13

F14

F15

F16

F17

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17

0.19 0.21 0.21 0.20 0.19 0.20 0.20 0.20 0.16 0.19 0.21 0.22 0.18 0.16 0.16 0.17 0.17

0.27 0.19 0.24 0.21 0.22 0.20 0.20 0.20 0.15 0.20 0.20 0.19 0.17 0.19 0.14 0.21 0.18

0.27 0.27 0.19 0.21 0.23 0.22 0.21 0.21 0.17 0.21 0.20 0.19 0.16 0.18 0.15 0.20 0.18

0.28 0.27 0.27 0.18 0.23 0.23 0.23 0.21 0.17 0.21 0.21 0.20 0.18 0.18 0.17 0.21 0.16

0.28 0.28 0.28 0.26 0.19 0.25 0.24 0.21 0.17 0.21 0.23 0.20 0.19 0.18 0.16 0.22 0.17

0.29 0.28 0.27 0.25 0.24 0.19 0.23 0.22 0.16 0.23 0.23 0.20 0.17 0.18 0.15 0.21 0.19

0.29 0.28 0.28 0.26 0.25 0.27 0.19 0.21 0.17 0.23 0.23 0.23 0.18 0.20 0.17 0.22 0.17

0.31 0.31 0.30 0.28 0.28 0.28 0.26 0.20 0.18 0.24 0.26 0.22 0.19 0.21 0.17 0.23 0.23

0.33 0.33 0.34 0.32 0.32 0.32 0.29 0.30 0.17 0.30 0.29 0.27 0.26 0.26 0.23 0.29 0.23

0.27 0.28 0.28 0.26 0.27 0.27 0.27 0.25 0.17 0.20 0.25 0.23 0.20 0.21 0.16 0.24 0.18

0.28 0.27 0.28 0.26 0.27 0.27 0.27 0.27 0.18 0.26 0.20 0.19 0.20 0.21 0.18 0.25 0.19

0.29 0.28 0.29 0.27 0.27 0.28 0.28 0.27 0.18 0.26 0.26 0.19 0.22 0.23 0.19 0.26 0.21

0.33 0.31 0.33 0.28 0.29 0.30 0.28 0.29 0.19 0.28 0.28 0.27 0.18 0.24 0.21 0.27 0.22

0.32 0.32 0.32 0.29 0.32 0.29 0.30 0.30 0.19 0.29 0.29 0.31 0.24 0.20 0.21 0.30 0.22

0.34 0.33 0.31 0.30 0.31 0.31 0.31 0.30 0.20 0.29 0.28 0.27 0.24 0.24 0.16 0.29 0.21

0.30 0.30 0.30 0.28 0.28 0.28 0.27 0.27 0.20 0.28 0.28 0.26 0.22 0.28 0.19 0.21 0.20

0.35 0.35 0.34 0.33 0.31 0.32 0.32 0.31 0.22 0.31 0.31 0.26 0.23 0.25 0.24 0.30 0.19

such as mobile phone platforms will help in improving food supply chain performance. Next, ‘Stability in business environment (F7)’ is very important to ensure price stability. Based on (E) score, ‘Private and foreign investment (F10)’ and ‘Investment in ICT infrastructure (F11)’ are very important in attracting global as well as local financial support in improving ICT infrastructure in SMEs of agri-food supply chains. This could be validated from the research of Faour-Klingbeil and Todd (2018). It suggested that collaboration between public and private sector's is crucial to leverage the expertise and infrastructure needed for higher quality food in a value chain context. Finally, ‘Revenue certainty (F8)’ with (E) score of 0.088,will help in boosting the confidence in SMEs and their partners to look at the options of upgrading their systems and become more competitive in the agri-food sector. Next, seven factors, ‘Encouragement and intention for ICT applications (F16)’; ‘HR recruitment and training (F12)’; ‘Organisational change/Re-engineering (F13)’; ‘Smooth integration and change management (F14)’; ‘Coordination between different departments (F15)’; ‘ICT integrated effective food supply chain (F17)’; and ‘Collaboration and strategic alliances across supply chain (F9)’ have been categorised as effect group factors. These factors, being with strong dependence help to develop efficient ICT applications in Indian food SMEs. ‘Encouragement and intention for ICT applications (F16)’ comes first in effect group factors. All above factors are important to build a workforce that can learn and handle the modern system, with the aim of improving existing or introducing new organisation structure to integrate ICT applications in SMEs. ‘HR and training (F12)’ comes next to F16. ‘Organisational change/Re-engineering (F13)’ comes next based

Table 5 Prominence and Net effect datasets for factors to ICT applications for sustainable growth in Indian food SMEs. Factors

Ri

Ci

Pi

Ei

Cause/Effect

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15 F16 F17

4.987 4.861 4.838 4.446 4.474 4.465 4.351 4.227 3.044 4.207 4.208 3.887 3.410 3.579 3.027 4.086 3.322

3.220 3.364 3.451 3.576 3.751 3.684 3.839 4.139 4.845 4.001 4.030 4.233 4.528 4.721 4.685 4.384 4.968

8.206 8.224 8.289 8.022 8.225 8.149 8.190 8.366 7.889 8.208 8.238 8.119 7.938 8.301 7.712 8.470 8.290

1.767 1.497 1.387 0.871 0.722 0.782 0.512 0.088 −1.801 0.207 0.178 −0.346 −1.119 −1.142 −1.658 −0.298 −1.646

Cause Cause Cause Cause Cause Cause Cause Cause Effect Cause Cause Effect Effect Effect Effect Effect Effect

‘Improved coordination between government and SMEs (F6)’, comes next. Luo et al. (2018) revealed in their research, ICT applications are crucial in improving business performance and collaboration initiatives. It means that ICT applications in food SMEs will help to improve coordination between government and SMEs. ‘Simple and secured ICT applications (F5)’ with (E) score of 0.668,

Fig. 2. The cause and effect diagram. 15

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

the nation's food security. Government support policies can help in the training for farmers and encourage cooperatives to assist them under risky conditions. In addition, there is a need to make stronger publicprivate partnership to encourage investments in the modernisation of food sector. Business organisations need to develop integration within the supply chain partners. Apart from this, adopting ICT applications in government procurement, logistics etc. will promote ICT service providers. Due to efficient use of ICT service providers; there may be a reduction in cost for various transactions within the business organisation. The expanded coordinated effort and key partnerships between developing elements will make ICT applications and frameworks achieve more players at SME levels, which would improve their operational efficiency. The collaboration and strategic alliances across supply chain helps to develop various capabilities in an organisational context. This study has some limitations. Firstly, the identification of key ICT application factors was very challenging. Grey based DEMATEL based model relies highly on the judgments of the decision team of experts, which may be biased. Findings may be further generalised and validated through empirical and case based studies.

on its (E) score, which will help in smooth integration of ICT applications in SMEs of agri-food supply chains and changing SMEs’ perspective towards ICT effective solutions. From (E) score, ‘Smooth integration and change management (F14)’, comes next, which will help in making effective ‘Coordination between different departments (F15)’. Next, ‘Coordination between different departments (F15)’ is very important to strategic collaboration across agri-food supply chain. With (E) score of -1.658, ‘ICT integrated effective food supply chain (F17)’ comes next. ICT integrated effective food supply chain will help to develop feedback mechanisms to improve traceability in supply chains (Rueda et al., 2017), which is going to help in achieving ‘Collaboration and strategic alliances across supply chain (F9)’ for higher sustainable growth in Indian SMEs of food sector. 5.1. Managerial implications This work suggests how different factors for ICT applications for sustainable growth in Indian food supply chain SMEs are interrelated and positioned along-with their cause and effect groups. This paper may facilitate policy makers, practitioners and supply chain managers to understand different key factors and their interdependence in effective adoption of ICT in SMEs. This is important as generally management emphasis on single or two important factors without considering the effect of other factors, which might be significant factors to implement ICT applications for green growth. Whilst, for improved resources management and enhanced strategic performance, food managers need to analyse factors in cause and effect group. The study outcome helps in exposing the causal relationships among the various factors in adding sustainability orientation in food businesses. Using Grey based DEMATEL framework, practitioners and managers may find quite simple to segregate important and unimportant factors that drives ICT applications for an effective resource management in SMEs in food sector. This study helps to promote a collaborative and cooperative culture within a supply chain. Management of SMEs can further figure out how to build up a vigorous and flexible data frameworks system to manage wastage of agricultural products and improving the utilisation of resources. In managing the ICT applications, the arrangement of innovative progression and up gradation is necessary. For this purpose training and education programs should also be started. It is also important to share information in the hierarchy for supply chain stability. Therefore, managers are advised to concentrate on building up the influential conditions to embrace ICT-driven Indian SMEs effectively.

Acknowledgement Authors are grateful to editor of the journal and reviewers for valuable suggestions to improve quality and content of the paper. References Aggarwal, S., Srivastava, M.K., 2016. Towards a grounded view of collaboration in Indian agri-food supply chains: a qualitative investigation. Br. Food J. 118 (5), 1085–1106. Ahumada, O., Villalobos, J.R., 2009. Application of planning models in the agri-food supply chain: a review. Eur. J. Oper. Res. 196 (1), 1–20. Akhtar, P., Khan, Z., 2015. The linkages between leadership approaches and coordination effectiveness: a path analysis of selected New Zealand-UK International agri-food supply chains. Br. Food J. 117 (1), 443–460. Akhtar, P., Tse, Y.K., Khan, Z., Rao-Nicholson, R., 2016. Data-driven and adaptive leadership contributing to sustainability: global agri-food supply chains connected with emerging markets. Int. J. Prod. Econ. 181, 392–401. Aung, M.M., Chang, Y.S., 2014. Traceability in a food supply chain: safety and quality perspectives. Food Control 39, 172–184. Badia-Melis, R., Mishra, P., Ruiz-García, L., 2015. Food traceability: new trends and recent advances. A review. Food Control 57, 393–401. Bai, C., Sarkis, J., 2013. A grey-based DEMATEL model for evaluating business process management critical success factors. Int. J. Prod. Econ. 146 (1), 281–292. Balaji, M., Arshinder, K., 2016. Modeling the causes of food wastage in Indian perishable food supply chain. Resour. Conserv. Recycl. 114, 153–167. Bamfo, P.A., Nyamekye, T.M., Ahenkan, A., 2019. The role of e-government in sustainable public procurement in developing countries: a systematic literature review. Resour. Conserv. Recycl. 142, 189–203. Barratt, M., 2004. Understanding the meaning of collaboration in the supply chain. Supply Chain. Manag. Int. J. 9 (1), 30–42. Bernard, A.B., Jensen, J.B., Redding, S.J., Schott, P.K., 2007. Firms in international trade. J. Econ. Perspect. 21 (3), 105–130. Bhagwat, R., Sharma, M.K., 2007. Information system architecture: a framework for a cluster of small-and medium-sized enterprises (SMEs). Prod. Plan. Control. 18 (4), 283–296. Bhandari, D., Singh, R.K., Garg, S.K., 2019. Prioritisation and evaluation of barriers intensity for implementation of cleaner technologies: framework for sustainable production. Resour. Conserv. Recycl. 146, 156–167. Bhaskaran, S., 2013. Structured case studies: information communication technology adoption by small-to-medium food enterprises. Br. Food J. 115 (3), 425–447. Bhatt, G., Emdad, A., Roberts, N., Grover, V., 2010. Building and leveraging information in dynamic environments: The role of IT infrastructure flexibility as enabler of organizational responsiveness and competitive advantage. Inf. Manag. 47 (7), 341–349. Bonneau, V., Copigneaux, B., 2017. Industry 4.0 in agriculture: focus on IoT aspects. European Commission, IDATE; Laurent Probst and Bertrand Pedersen, PwC. Brand Equity, 2016. 98% Of Grocery Retail Market is Controlled by Kirana Stores: Study. Online available at: (last accessed: July 1, 2018).. https://brandequity. economictimes.indiatimes.com/news/business-of-brands/98-of-grocery-retailmarket-is-controlled-by-kirana-stores-study/50797310. Chang, H.H., Tsai, Y.C., Hsu, C.H., 2013. E-procurement and supply chain performance. Supply Chain Manag. Int. J. 18 (1), 34–51. Chen, K.Z., Joshi, P.K., Cheng, E., Birthal, P.S., 2015. Innovations in financing of agri-food value chains in China and India: lessons and policies for inclusive financing. China Agric. Econ. Rev. 7 (4), 616–640. Cui, L., Chan, H.K., Zhou, Y., Dai, J., Lim, J.J., 2018. Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory

6. Conclusions The Indian food sector is predominantly thriving with SME players such as farmers, agriculturist, transporters, food processors, warehouse providers and part from scrupulous intermediaries; and years of chronic inefficiency. Backwardness has destabilised the opportunities that could have been extracted from the agriculture cost towards GDP of the country. ICT applications may help in improving collaboration between different stakeholders and results in enhanced food supply performance to underpin green and sustainable development. This work puts into practice effective sustainable growth in Indian SMEs business aspects by evaluating the key factors to ICT applications taking a perspective of food supply chain. The current work uses Grey-DEMATEL-based technique to investigate the key factors and their cause and effect relations. From the analysis, ‘Government initiatives and policies (F1)’; ‘Public-private partnership (F2)’; and ‘Encouragement to ICT service provider (F3)’ are top most influential cause group factors. While, ‘ICT integrated effective food supply chain (F17)’, ‘Coordination between different departments (F15)’, and ‘Collaboration and strategic alliances across supply chain (F9)’ are highest influenced factors. The government is a central body in 16

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

1906–1918. Li, Y., Kramer, M.R., Beulens, A.J.M., van der Vorst, J.G.A.J., 2006. Using data mining to improve operations management in food supply networks. International Agri-food Chains and Networks: Management and Organization. Wageningen Academic Publishers, pp. 163–177. Luo, W., Shi, Y., Venkatesh, V.G., 2018. Exploring the Factors of Achieving Supply Chain Excellence: A New Zealand Perspective. Production Planning & Control, pp. 1–13. Luthra, S., Mangla, S.K., 2018. When strategies matter: adoption of sustainable supply chain management practices in an emerging economy’s context. Resour. Conserv. Recycl. 138, 194–206. Luthra, S., Govindan, K., Mangla, S.K., 2017. Structural model for sustainable consumption and production adoption—a grey-DEMATEL based approach. Resour. Conserv. Recycl. 125, 198–207. Luthra, S., Mangla, S.K., Garg, D., Kumar, A., 2018a. Internet of things (IoT) in agriculture supply chain management: a developing country perspective. Emerging Markets From a Multidisciplinary Perspective. Springer, Cham, pp. 209–220. Luthra, S., Mangla, S.K., Shankar, R., Prakash Garg, C., Jakhar, S., 2018b. Modelling Critical Success Factors for Sustainability Initiatives in Supply Chains in Indian Context Using Grey-DEMATEL. Production Planning & Control, pp. 1–24. Mangina, E., Vlachos, I.P., 2005. The changing role of information technology in food and beverage logistics management: beverage network optimisation using intelligent agent technology. J. Food Eng. 70 (3), 403–420. Mangla, S.K., Kumar, P., Barua, M.K., 2015. Risk analysis in green supply chain using fuzzy AHP approach: a case study. Resour. Conserv. Recycl. 104, 375–390. Mangla, S.K., Govindan, K., Luthra, S., 2016. Critical success factors for reverse logistics in Indian industries: a structural model. J. Clean. Prod. 129, 608–621. Mangla, S.K., Luthra, S., Rich, N., Kumar, D., Rana, N.P., Dwivedi, Y.K., 2018. Enablers to implement sustainable initiatives in agri-food supply chains. Int. J. Prod. Econ. 203, 379–393. Manning, L., Baines, R.N., 2004. Effective management of food safety and quality. Br. Food J. 106 (8), 598–606. Mathur, A., Mittal, M.L., Dangayach, G.S., 2012. Improving productivity in indian SMEs. Prod. Plan. Control. 23 (10-11), 754–768. Maurya, U.K., Mishra, P., Anand, S., Kumar, N., 2015. Corporate identity, customer orientation and performance of SMEs: exploring the linkages. IIMB Manag. Rev. 27 (3), 159–174. Mishra, N., Singh, A., Rana, N.P., Dwivedi, Y.K., 2017. Interpretive structural modelling and fuzzy MICMAC approaches for customer centric beef supply chain: application of a big data technique. Prod. Plan. Control. 28 (11-12), 945–963. Mohezar, S., Nor, M.N.M., 2014. Could supply chain technology improve food operators’ innovativeness? A developing country’s perspective. Trends Food Sci. Technol. 38 (1), 75–82. Narula, S.A., 2017. Revolutionizing food supply chains of Asia through ICTs. Sustain. Challenges Agrofood Sector 212. National Manufacturing Competitiveness Council, 2012. Enhancing Firm Level Competitive Indian Food and Agro Processing Industry: Strategies and Road Map Development. New Delhi. . Ngai, E.W.T., Lai, K.H., Cheng, T.C.E., 2008. Logistics information systems: the Hong Kong experience. Int. J. Prod. Econ. 113 (1), 223–234. NRAI, 2013. The India Food Service Report. Online available at:. . http://nrai.org/ downloads/reports/. O’Reilly, S., Kumar, A., Adam, F., 2015. The role of hierarchical production planning in food manufacturing SMEs. Int. J. Oper. Prod. Manage. 35 (10), 1362–1385. Pan, X., Zhang, J., Li, C., Quan, R., Li, B., 2018. Exploring dynamic impact of foreign direct investment on China’s CO $$_{2}$$ 2 emissions using markov-switching vector error correction model. Comput. Econ. 52 (4), 1139–1151. Pramatari, K., 2007. Collaborative supply chain practices and evolving technological approaches. Supply Chain. Manag. Int. J. 12 (3), 210–220. Pramatari, K., 2015. Information technology for food supply chains. Supply Chain Manag. Sustain. Food Netw. 183–203. Rais, M., Acharya, S., Vanloon, G.W., 2014. Food processing industry: opportunities in north east region of India. Nehu J. 12 (1), 37–51. Rajesh, R., Ravi, V., 2015. Modeling enablers of supply chain risk mitigation in electronic supply chains: a grey–DEMATEL approach. Comput. Ind. Eng. 87, 126–139. Raut, R.D., Luthra, S., Narkhede, B.E., Mangla, S.K., Gardas, B.B., Priyadarshinee, P., 2019. Examining the performance oriented indicators for implementing green management practices in the Indian agro sector. J. Clean. Prod. 215, 926–943. Regattieri, A., Gamberi, M., Manzini, R., 2007. Traceability of food products: general framework and experimental evidence. J. Food Eng. 81 (2), 347–356. Ritchie, B., Brindley, C., 2000. Disintermediation, disintegration and risk in the SME global supply chain. Manage. Decis. 38 (8), 575–583. Riviere, J.E., Buckley, G.J. (Eds.), 2012. Ensuring Safe Foods and Medical Products Through Stronger Regulatory Systems Abroad. National Academies Press. Rueda, X., Garrett, R.D., Lambin, E.F., 2017. Corporate investments in supply chain sustainability: selecting instruments in the agri-food industry. J. Clean. Prod. 142, 2480–2492. Saguy, I.S., Sirotinskaya, V., 2014. Challenges in exploiting open innovation’s full potential in the food industry with a focus on small and medium enterprises (SMEs). Trends Food Sci. Technol. 38 (2), 136–148. Sahay, B.S., Gupta, J.N., Mohan, R., 2006. Managing supply chains for competitiveness: the Indian scenario. Supply Chain. Manag. Int. J. 11 (1), 15–24. Sambamurthy, V., Bharadwaj, A., Grover, V., 2003. Shaping agility through digital options: reconceptualising the role of information technology in contemporary firms. Mis Q. 27 (2), 237–263. Schroeder, T.C., Tonsor, G.T., 2012. International cattle ID and traceability: competitive implications for the US. Food Policy 37 (1), 31–40.

(DEMATEL). J. Bus. Res. https://doi.org/10.1016/j.jbusres.2018.03.031. D & B Report, 2015. A Report on Emerging SMEs of India- An Overview of Indian Food Process Industry. Available at: (last accessed: June 12, 2016).. https://www.dnb.co. in/Food%20Processing/overview.asp. Dandage, K., Badia-Melis, R., Ruiz-García, L., 2017a. Indian perspective in food traceability: a review. Food Control 71, 217–227. Dandage, K., Badia-Melis, R., Ruiz-García, L., 2017b. Indian perspective in food traceability: a review. Food Control 71, 217–227. Dania, W.A.P., Xing, K., Amer, Y., 2018. Collaboration behavioural factors for sustainable agri-food supply chains: a systematic review. J. Clean. Prod. 186, 851–864. Dora, M., Gellynck, X., 2015. House of lean for food processing SMEs. Trends Food Sci. Technol. 44 (2), 272–281. Dora, M., Kumar, M., Gellynck, X., 2016. Determinants and barriers to lean implementation in food-processing SMEs–a multiple case analysis. Prod. Plan. Control. 27 (1), 1–23. Dyerson, R., Harindranath, G., Barnes, D., 2009. National survey of SMEs’ use of IT in four sectors. Electron. J. Inform. Syst. Eval. 12 (1), 39–50. Faisal, M.N., Talib, F., 2016. Implementing traceability in Indian food-supply chains: an interpretive structural modelling approach. J. Foodserv. Bus. Res. 19 (2), 171–196. FAO, 2017. The State of Food and Agriculture, Leveraging Food Systems for Inclusive Rural Transformation. Retrieved from (last accessed: March 11, 2019).. http:// www.fao.org/3/a-i7658e.pdf. Faour-Klingbeil, D., Todd, E.C., 2018. A review on the rising prevalence of International standards: threats or opportunities for the agri-food produce sector in developing countries, with a focus on examples from the MENA region. Foods 7 (3), 33–38. FICCI, 2010. Survey on Challenges in Food Processing Sector. A Report by FICCI. Mumbai. . Filipescu, D.A., Rialp, A., Rialp, J., 2009. Internationalisation and technological innovation: empirical evidence on their mutual relationship. New Challenges to International Marketing. Emerald Group Publishing Limited, pp. 125–154. Flynn, B.B., Huo, B., Zhao, X., 2010. The impact of supply chain integration on performance: a contingency and configuration approach. J. Oper. Manag. 28 (1), 58–71. Fritz, M., Schiefer, G., 2009. Tracking, tracing, and business process interests in food commodities: a multi-level decision complexity. Int. J. Prod. Econ. 117 (2), 317–329. Gabus, A., Fontela, E., 1972. World Problems, an Invitation to Further Thought Within the Framework of DEMATEL. Battelle Geneva Research Center, Geneva, Switzerland, pp. 1–8. Gaukler, G.M., 2010. Preventing avoidable stock outs: the impact of item-level RFID in retail. J. Bus. Ind. Mark. 25 (8), 572–581. Ghadge, A., Kaklamanou, M., Choudhary, S., Bourlakis, M., 2017. Implementing environmental practices within the Greek dairy supply chain: drivers and barriers for SMEs. Ind. Manag. Data Syst. 117 (9), 1995–2014. Gong, M., Simpson, A., Koh, L., Tan, K.H., 2018. Inside out: the interrelationships of sustainable performance metrics and its effect on business decision making: theory and practice. Resour. Conserv. Recycl. 128, 155–166. Govindan, K., 2018. Sustainable consumption and production in the food supply chain: a conceptual framework. Int. J. Prod. Econ. 195, 419–431. Gunasekaran, A., Ngai, E.W., 2008. Adoption of e-procurement in Hong Kong: an empirical research. Int. J. Prod. Econ. 113 (1), 159–175. Halloran, A., Clement, J., Kornum, N., Bucatariu, C., Magid, J., 2014. Addressing food waste reduction in Denmark. Food Policy 49, 294–301. Hendricks, K.B., Singhal, V.R., Stratman, J.K., 2007. The impact of enterprise systems on corporate performance: a study of ERP, SCM, and CRM system implementations. J. Oper. Manag. 25 (1), 65–82. Hobbs, J.E., Bailey, D., Dickinson, D.L., Haghiri, M., 2005. Traceability in the 756 Canadian red meat sector: do consumers care? Can. J. Agric. 53 (1), 47–65 757 Economics/Revue canadienne d'agroeconomie. Hsu, C.W., Kuo, T.C., Chen, S.H., Hu, A.H., 2013. Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. J. Clean. Prod. 56, 164–172. Jakhar, S.K., Rathore, H., Mangla, S.K., 2018. Is lean synergistic with sustainable supply chain? An empirical investigation from emerging economy. Resour. Conserv. Recycl. 139, 262–269. Jayaram, J., Dixit, M., Motwani, J., 2014. Supply chain management capability of small and medium sized family businesses in India: a multiple case study approach. Int. J. Prod. Econ. 147, 472–485. Karipidis, P., Athanassiadis, K., Aggelopoulos, S., Giompliakis, E., 2009. Factors affecting the adoption of quality assurance systems in small food enterprises. Food Control 20 (2), 93–98. Kotsanopoulos, K.V., Arvanitoyannis, I.S., 2017. The role of auditing, food safety, and food quality standards in the food industry: a review. Compr. Rev. Food Sci. Food Saf. 16 (5), 760–775. Kritchanchai, D., 2004. Assessing responsiveness of the food industry in Thailand. Ind. Manag. Data Syst. 104 (5), 384–395. Kumar, A., Dixit, G., 2018. Evaluating critical barriers to implementation of WEEE management using DEMATEL approach. Resour. Conserv. Recycl. 131, 101–121. Kumar, S., Nigmatullin, A., 2011. A system dynamics analysis of food supply chains – case study with non-perishable products. Simul. Model. Pract. Theory 19 (10), 2151–2168. Kumar, R., Agrawal, R., Sharma, V., 2013. e-Applications in Indian agri-food supply chain: relationship among enablers. Glob. Bus. Rev. 14 (4), 711–727. Kumar, R., Singh, K., Shankar, R., 2014. Strategy development by Indian SMEs for improving coordination in supply chain: an empirical study. Compet. Rev. Int. Bus. J. Inc. J. Glob. Compet. 24 (5), 414–432. Kurnia, S., Choudrie, J., Mahbubur, R.M., Alzougool, B., 2015. E-commerce technology adoption: a Malaysian grocery SME retail sector study. J. Bus. Res. 68 (9),

17

Resources, Conservation & Recycling 147 (2019) 10–18

R.K. Singh, et al.

181–199. Thakkar, J., Kanda, A., Deshmukh, S.G., 2009. Supply chain management for SMEs: a research introduction. Manag. Res. News 32 (10), 970–993. Thakkar, J., Kanda, A., Deshmukh, S.G., 2013. Supply chain issues in SMEs: select insights from cases of Indian origin. Prod. Plan. Control. 24 (1), 47–71. Thakur, V., Mangla, S.K., 2019. Change management for sustainability: evaluating the role of human, operational and technological factors in leading Indian firms in home appliances sector. J. Clean. Prod. 213, 847–862. Thakur, M., Sørensen, C.F., Bjørnson, F.O., Forås, E., Hurburgh, C.R., 2011. Managing food traceability information using EPCIS framework. J. Food Eng. 103 (4), 417–433. Trienekens, J.H., Wognum, P.M., Beulens, A.J., van der Vorst, J.G., 2012. Transparency in complex dynamic food supply chains. Adv. Eng. Inform. 26 (1), 55–65. Tseng, M.L., Chiu, A.S., Liang, D., 2017. Sustainable consumption and production in business decision-making models. Resour. Conserv. Recycl. 128, 118–121. Vaaland, T.I., Heide, M., 2007. Can the SME survive the supply chain challenges? Supply Chain. Manag. Int. J. 12 (1), 20–31. Verdouw, C.N., Wolfert, J., Beulens, A.J., Rialland, A., 2016. Virtualization of food supply chains with the internet of things. J. Food Eng. 176, 128–136. Vickery, S.K., Jayaram, J., Droge, C., Calantone, R., 2003. The effects of an integrative supply chain strategy on customer service and financial performance: an analysis of direct versus indirect relationships. J. Oper. Manag. 21 (5), 523–539. Vlachos, I.P., 2014. A hierarchical model of the impact of RFID practices on retail supply chain performance. Expert Syst. Appl. 41 (1), 5–15. Vlachos, I., 2015. Applying lean thinking in the food supply chains: a case study. Prod. Plan. Control. 26 (16), 1351–1367. WTO, 2004. World Trade Report. World Trade Organisation, Geneva. Xia, X., Govindan, K., Zhu, Q., 2015. Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. J. Clean. Prod. 87, 811–825. Zhong, R., Xu, X., Wang, L., 2017. Food supply chain management: Systems, implementations, and future research. Ind. Manag. Data Syst. 117 (9), 2085–2114.

Shao, J., Taisch, M., Ortega-Mier, M., 2016. A grey-DEcision-MAking Trial and Evaluation Laboratory (DEMATEL) analysis on the barriers between environmentally friendly products and consumers: practitioners’ viewpoints on the European automobile industry. J. Clean. Prod. 112, 3185–3194. Sharma, Y.K., Mangla, S.K., Patil, P.P., Liu, S., 2019. When challenges impede the process: for circular economy-driven sustainability practices in food supply chain. Manage. Decis (in press). Shirani, M., Demichela, M., 2015. IT system in the food supply chain safety, application in SMEs sector. World Acad. Sci. Eng. Technol. Int. J. Soc. Behav. Educ. Econ. Manag. Eng. 9, 2761–2765. Singh, R.K., 2014. Coordination in food supply chain: a framework. Int. J. Inf. Syst. Supply Chain. Manag. 7 (3), 104–117. Singh, R.K., Garg, S.K., Deshmukh, S.G., 2008. Implementation of information technology: evidence from Indian SMEs. Int. J. Enterp. Netw. Manag. 2 (3), 248–267. Singh, R.K., Garg, S.K., Deshmukh, S.G., 2009. The competitiveness of SMEs in a globalized economy: observations from China and India. Manag. Res. Rev. 33 (1), 54–65. Song, M., Wang, S., 2017. Participation in global value chain and green technology progress: evidence from big data of Chinese enterprises. Environ. Sci. Pollut. Res. Int. 24 (2), 1648–1661. Song, M., Wang, S., 2018. Market competition, green technology progress and comparative advantages in China. Manage. Decis. 56 (1), 188–203. Song, M., Wang, J., Zhao, J., 2018. Coal endowment, resource curse, and high coalconsuming industries location: analysis based on large-scale data. Resour. Conserv. Recycl. 129, 333–344. Stefansson, G., Tilanus, B., 2001. Tracking and tracing: principles and practice. Int. J. Serv. Technol. Manag. 2 (3-4), 187–206. Su, C.M., Horng, D.J., Tseng, M.L., Chiu, A.S., Wu, K.J., Chen, H.P., 2016. Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach. J. Clean. Prod. 134, 469–481. Tatoglu, E., Bayraktar, E., Golgeci, I., Koh, S.L., Demirbag, M., Zaim, S., 2016. How do supply chain management and information systems practices influence operational performance? Evidence from emerging country SMEs. Int. J. Logist. Res. Appl. 19 (3),

18