Reverse logistics capabilities and supply chain performance in a developing country context

Figures & data

Figure 1. A hypothesized conceptual framework.

Table 1. Validity and reliability test for factors and items.

Factors (Reliabilities)	Items	Factor loadings
Logistics Information Management systems (0.828)	My company has information systems to record, track and respond to return service requests from customers.	0.665
	My company’s information systems are flexible to allow the infusion of new methodologies, tools and techniques for handling returns.	0.724
	My company’s information systems can reconcile stocks returned by customers.	0.709
	My company can effectively collect and process the information on returned products.	0.802
	My company can share information on returned products between departments.	0.659
	My company has established information integration with its suppliers and customers.	0.805
Process formalization capability (0.878)	My company uses written procedures and guidelines for monitoring and controlling the return process.	0.716
	My company clearly communicates the return-processing procedures to customers on receipt of return requests.	0.787
	My company uses written procedures and guidelines for analyzing the disposal process of returned products.	0.769
	My company documents responsibilities, authority, and accountability of return processes in personnel job descriptions.	0.829
	My company has highly formalized channels of communication (reporting structure) for return processes.	0.815
	My company has skilled and qualified personnel to handle return processes.	0.686
Flexibility capability (0.836)	My company has the capability to have collection schedules changed for returns.	0.780
	My company has the capability to handle short-term or long-term scheduling of returning products.	0.703
	My company has the capability to outsource the return process to a third party.	0.639
	My company has the capability to handle small and large capacities of returned products economically.	0.792
	My company can change warehouse storage capacity for returned products quickly.	0.845
	My company has the capability to economically disassemble smaller and larger lots of returned products.	0.871
Supply chain performance (0.943)	My company is able to have the right product returned.	0.817
	My company is able to execute the return process on the scheduled time.	0.816
	My company is able to have the right quantity of product returned.	0.848
	My company is able to achieve an average return cycle time as per internal procedures.	0.776
	My company is able to reduce the average time associated with authorizing the return of products.	0.710
	My company is able to reduce the time taken to issue credit note for returned products.	0.770
	My company is able to replace quantities returned from customers.	0.739
	My company is able to minimize the overall value at risk in handling returns.	0.784
	My company is able to reduce the time taken to recover from the disruption of returns.	0.827
Top management support (0.890)	Top Management considers reverse logistics as an important strategy to supply chain performance.	0.788
	Top Management commits resources to the development of reverse logistics capabilities.	0.807
	Top management directly involves in the reverse logistics activities	0.673

Table 2. Demographic information of the respondents.

Variable	Category	Number	Percentage
Gender	Female	34	33.3
	Male	68	67.7
Age	20–30 years	30	29.4
	31–35 years	21	20.6
	36–40 years	18	17.6
	41–45 years	18	17.6
	Above 45 years	15	14.7
Education	Diploma	4	3.9
	Bachelor	74	72.5
	Masters	21	20.6
	PGD	2	2.0
	PhD	1	1.0
Length in service	Below 3 years	14	13.7
	3–6 years	25	24.5
	Above 6 years	63	61.8
Department of Respondent	Warehouse	10	9.8
	Procurement	12	11.8
	Sales	33	32.4
	Regulatory affairs	41	40.2
	Marketing	6	5.9
Category of Organization	Retail	60	58.8
	Wholesale	37	36.3
	Manufacturing	5	4.9

Table 3. Model findings on the effect of logistics information management capability on supply chain performance.

Independent Variables	Beta Coefficients	Std. Errors	P-value	Adjusted R^2	ANOVA F (P-value)
Constant	.269	.216	.216
Logistics information management capability	.843	.067	.000	.609	158.140(0.000)

Table 4. Model findings on the effect of process formalisation capability on supply chain performance.

Model	R		R Square		Adjusted R Square	Std. Error of the Estimate
Model Summary
1	.723^a		.522		.517	.60831
Model		Sum of Squares	df	Mean Square	F	Sig.
ANOVA
1	Regression	40.440	1	40.440	109.285	.000
	Residual	37.004	100	.370
	Total	77.445	101
		Unstandardized Coefficients		Standardized Coefficients
Model		B	Std. Error	Beta	t	Sig.
Coefficients
1	(Constant)	.562	.232		2.427	.017
	Process formalisation capability	.852	.081	.723	10.454	.000
Independent Variables	Beta Coefficients		Std. Errors	P-value	Adjusted R^2	ANOVA F (P-value)
Constant	.562		.232	.017
Process formalisation capability	.852		.081	.000	.517	109.285 (0.000)

^aPredictors: (Constant), Process formalisation capability

^bDependent Variable: Supply chain performance

^aDependent Variable: Supply chain performance

^bPredictors: (Constant), Process formalisation capability

^aDependent Variable: Supply chain performance

Table 5. Model findings on the effect of flexibility capability on supply chain performance.

Independent Variables	Beta Coefficient s	Std. Errors	P-value	Adjusted R^2	ANOVA F (P-value)
Constant	.326	.258	.211
Flexibility capability	.802	.078	.000	.507	105.013 (0.000)

Table 6. Model goodness of fit with supply chain performance as the dependent variable and reverse logistics capabilities, top management support, and interaction term as independent.

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
Model Summary^c
1	.835^a	.697	.691	.48697	.697	113.791	2	99	.000
2	.835^b	.697	.688	.48893	.001	.206	1	98	.651

^aPredictors: (Constant), Top management support, Reverse logistics capabilities

^bPredictors: (Constant), Top management support, Reverse logistics capabilities, the Interaction term

^cDependent Variable: Supply chain performance

Table 7. Model coefficients with supply chain performance as the dependent variable and reverse logistics capabilities, top management support and interaction term as independent.

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
Coefficients
1	(Constant)	−.321	.219		−1.466	.146
	Reverse logistics capabilities	.924	.097	.735	9.536	.000
	Top management support	.118	.068	.135	1.749	.083
2	(Constant)	−.104	.527		−.198	.844
	Reverse logistics capabilities	.835	.220	.664	3.801	.000
	Top management support	.054	.157	.061	.343	.732
	Interaction Term (Reverse logistics capabilities * Top management support)	.025	.055	.135	.454	.651

a. Dependent Variable: Supply chain performance