Information Sharing and Supply Chain Performance

Information sharing within the supply chain will help supply chain participants to make wise decision about their future business plans (I1 and I6). It will help firms to coordinate with each other in order to achieve mutual benefits which will eventually improve their relationship (I6). Information when shared at the right time will help supply chain participants to improve their supply chain performance which will eventually enhance the performance of the entire chain. It will help supply chain partners to reduce their cost, improve the quality of their product/service, delivery and flexibility.

One participant (I2) explained how information sharing will affect supply chain performance,

“when firms receive information from their customers about the quantity, the time and the

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delivery date. When the distributor or the wholesaler receives the dispatch/delivery and tracking/tracing information, they can plan for delivery at their end. On the basis of the received information, they can plan accordingly to fulfil their commitment to their customers

or put it on hold and inform them. In this way the chances of losing business is also low.”

“When information is correct, planning will be correct, result will be correct and hence we

get benefit,” stated another participant (I1). This example shows how information sharing will

affect delivery, flexibility and the quality of service of supply chain participants.

Information sharing will also have a significant effect on cost. One participant explained how their cost gets affected because of late or wrong information. “Being a landlocked country, Nepal is using Calcutta Port in India, a different territory. When importing raw materials,

our supply chain partners like *** (identity hidden due to ethical reasons), that’s our custom

clearing agent, and our transporter might give us the wrong information about the vessel berth. If they will not update us on time, we might have to pay the detention and demurrage

charge,” – Senior Manager (I5). This is an example which illustrates how supply chain cost is

affected due to information sharing. Improvement in supply chain performance will improve the overall firm performance because it has a direct effect on firm performance such as profitability (I1, I2, I4, I5, I6, I7, I8 and I9). While smooth supply chain gives a positive result to a firm’s profitability, “for logistics companies supply chain performance will have

100% effect on firm performance,” pinpointed one participant (I8).

5.4 Summary

This chapter explained in detail how the quantitative and quantitative data were analysed in this study to answer the research questions. The quantitative data analysis process was explained first followed by the qualitative analysis. The quantitative analysis phase included descriptive analysis, exploratory factor analysis for convergent validity, discriminant validity and unidimensionality, Cronbach’s alpha for reliability test and regression analyses to test the relationship between constructs.

Data coding and data screening/cleaning process to make the data ready for further analysis in SPSS were explained first. The demographic information was analysed to reveal the suitability of the respondents. A cross-tabulation of three demographic variables business sector, international trade and number of employees was also carried out. The descriptive

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analysis revealed that the respondent pool meets the criteria of the target population in terms of business sector, respondent’s position/experience and size of the company (number of employees). Majority of the respondents are manufacturers, who in the context of Nepal own relatively large companies compared to other business sectors (retailers, wholesalers or logistics service providers). Other sectors usually are small or medium sized with a few big players. The involvement of significantly large number of companies in international trade shows that import/export is an important business activity for Nepalese firms. This also means that information sharing may be critical in dealing with international partners and hence, Nepalese firms should pay considerable attention towards enhancing it.

The measurement instrument was assessed through reliability, unidimensionality, convergent validity and discriminant validity of the measured items. Exploratory factor analysis was conducted to ensure unidimensionality and validity of the survey instrument. Trial-and-error method was employed for selecting the final factor structure. EFA was re-run nine times, deleting different items one at a time. This technique allowed the researcher to check different factor structure and select the one that is most appropriate. After discarding the items with loadings below 0.5 and items with cross loadings, a factors structure with sixteen factors was extracted. All items loaded significantly and substantially on their underlying constructs confirming unidimensionality, convergent validity and discriminant validity. The factors scores were computed from EFA via Anderson-Rubin method. Cronbach’s alpha values were calculated for each construct. All, except three constructs (0.66 – 0.68), had alpha values greater or equal to 0.7 which were all retained for further analysis.

Multiple regression analysis was applied to find out the significant factors affecting operational and strategic information sharing and the effect of information sharing on supply chain performance. The tests for the assumptions confirmed that the data was suitable for regression analysis. The regression analysis results suggested that operational information sharing was affected by relationship, intra- and inter-organisational factors while strategic information sharing was affected by factors across all four categories. Furthermore, interaction routines, organisational compatibility, incentives, project payoffs, commitment, personal connection and top management commitment have significant effect on operational information sharing. Whereas strategic information sharing was significantly affected by interaction routines, government support, personal connection and monitoring. The regression analysis also examined the effect of information sharing on supply chain performance. The

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results show that both operational and strategic information sharing affects delivery and flexibility performance only. Information sharing had the greatest impact on flexibility as the model explained 18% of the variation in flexibility due to information sharing.

Content analysis was used to analyse the qualitative data in order to supplement the quantitative results. The qualitative results revealed that factors such as interaction routines, government support, supply network configuration, supply uncertainty, information quality, benefits, commitment, personal connection, organisational compatibility, reputation, and market orientation were considered by the interviewees as important factors to influence information sharing. It explained how supply chain participants in Nepal perceived information sharing with their partners and their outlooks on how it affects their supply chain performance. Furthermore, it explained the status of IT in Nepal and the barriers towards its successful implementation. While the qualitative results were in-line with the quantitative results, it identified additional factors that were not identified quantitatively. This will be discussed in detail in the next chapter.

The next chapter will merge the quantitative and qualitative results and then discuss the findings in detail. It will compare the results with the previous studies and explain the likely reasons for the similarities and differences.

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