Development of sustainable logistics performance model using system dynamics in urban logistics service companies in Indonesia

Figures & data

Figure 1. Pillars of sustainability.

Figure 2. Interaction of sustainability in logistics services.

Source: (Hosseini-Motlagh et al., 2019).

Figure 3. Stages of explanatory study.

Figure 4. Conceptual framework for the relationship between latent variables.

Notes:Independent Variables:Economic Management (X1)Customer Management (X2)Environmental Management (X3)Social Management (X4)

Table 1. Hypothesis testing

Hypothesis	Statement	Test Criteria i(α=5%)
Ha1 : $\mathit{\rho }$ ≠ 0	There is an influence of ieconomic imanagement on isosial imanagement of logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha2 : $\mathit{\rho }$ ≠ 0	There is an influence of icustomer imanagement on isocial imanagement of logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha3 : $\mathit{\rho }$ ≠ 0	There is an influence of icustomer imanagement on ieconomic imanagement of logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha4 : $\mathit{\rho }$ ≠ 0	There is an influence of ienvironmental i imanagement on ieconomic imanagement of logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha5 : $\mathit{\rho }$ ≠ 0	There is an influence of ieconomic imanagement on iSustainability	Reject Ha1 if t-calculated < t-table (1.96)
Ha6 : $\mathit{\rho }$ ≠ 0	There is an influence of icustomer imanagement on iSustainability logistics model in logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha7 : $\mathit{\rho }$ ≠ 0	There is an influence of ienviromental imanagement on Sustainability logistics model in logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)
Ha8 : $\mathit{\rho }$ ≠ 0	There is an influence of social imanagement on iSustainability logistics model in logistics services companies in Indonesia	Reject Ha1 if t-calculated < t-table (1.96)

Table 2. Reliability assessment

Variable	alpha	rhoC	AVE
Reducing Environmental Problems	0.789	0.855	0.546
Reducing Emissions	0.799	0.855	0.500
Infrastructure Protection	0.709	0.805	0.455
Service Management	0.807	0.860	0.508
Use of Information Technology	0.867	0.909	0.714
Customer Segmentation	0.742	0.852	0.658
Traffic Congestion Reduction	0.789	0.849	0.487
Profitability Goals	0.837	0.879	0.512
Financial Performance	0.814	0.871	0.577
Health Purposes	0.762	0.846	0.580
Safety Purposes	0.743	0.830	0.496
Employment Practices	0.664	0.799	0.506

Source: Processed Data (2023).

Table 3. Fornell-Lacker test

Variable	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12
V1	0.6266
V2	0.4657	0.5479
V3	0.3696	0.5899	0.5652
V4	0.5029	0.4644	0.4272	0.5473
V5	0.4387	0.5589	0.5030	0.6140	0.6354
V6	0.3986	0.3772	0.3470	0.5005	0.4873	0.6902
V7	0.4337	0.5294	0.4234	0.4639	0.5445	0.3526	0.5347
V8	0.5340	0.5735	0.5416	0.4892	0.5541	0.4543	0.5897	0.5641
V9	0.4560	0.4795	0.4277	0.4301	0.5368	0.3994	0.5126	0.5747	0.6054
V10	0.3988	0.5256	0.3449	0.4076	0.4474	0.4402	0.4715	0.4373	0.3835	0.6477
V11	0.4743	0.5295	0.5444	0.5155	0.6643	0.4975	0.4949	0.6053	0.5127	0.4350	0.5579
V12	0.4929	0.4869	0.3614	0.4820	0.5549	0.3638	0.4803	0.5031	0.4532	0.4789	0.5006	0.6178

Source : Processed data (2023).

Table 4. Heterotrait-monotrait Ratio assessment

Variable	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12
V1
V2	0.941
V3	0.874	1.009
V4	0.872	0.743	0.730
V5	0.859	0.911	0.837	0.809
V6	0.876	0.773	0.863	0.936	0.760
V7	0.788	0.819	0.717	0.593	0.741	0.742
V8	0.950	0.875	0.811	0.799	0.852	0.897	0.952
V9	0.805	0.707	0.668	0.600	0.736	0.691	0.881	0.921
V10	0.830	0.881	0.903	0.685	0.814	0.866	0.754	0.774	0.740
V11	0.911	0.961	0.983	0.822	0.937	0.952	0.677	0.881	0.797	0.994
V12	1.027	0.963	0.807	0.964	1.019	0.882	0.807	0.974	0.777	0.978	0.936

Source : Processed data (2023).

Table 5. Correlation assessment

Variable	V1	V2	V3	V4	V5	V6	V7	V8	V9	V10	V11	V12
V1	1.000	0.733	0.672	0.704	0.700	0.690	0.660	0.788	0.657	0.672	0.690	0.754
V2	0.733	1.000	0.755	0.602	0.762	0.601	0.690	0.746	0.595	0.713	0.723	0.707
V3	0.672	0.755	1.000	0.589	0.683	0.673	0.613	0.679	0.533	0.689	0.695	0.571
V4	0.704	0.602	0.589	1.000	0.691	0.734	0.498	0.662	0.507	0.580	0.659	0.739
V5	0.700	0.762	0.683	0.691	1.000	0.616	0.644	0.736	0.627	0.701	0.759	0.789
V6	0.690	0.601	0.673	0.734	0.616	1.000	0.600	0.705	0.550	0.672	0.726	0.632
V7	0.660	0.690	0.613	0.498	0.644	0.600	1.000	0.800	0.716	0.623	0.541	0.595
V8	0.788	0.746	0.679	0.662	0.736	0.705	0.800	1.000	0.772	0.656	0.714	0.734
V9	0.657	0.595	0.533	0.507	0.627	0.550	0.716	0.772	1.000	0.597	0.628	0.580
V10	0.672	0.713	0.689	0.580	0.701	0.672	0.623	0.656	0.597	1.000	0.760	0.719
V11	0.690	0.723	0.695	0.659	0.759	0.726	0.541	0.714	0.628	0.760	1.000	0.690
V12	0.754	0.707	0.571	0.739	0.789	0.632	0.595	0.734	0.580	0.719	0.690	1.000

Source : Processed data (2023).

Table 6. Model results

No	Path	Original Est.	Std Deviation	T Stat.	2.5% CI	97.5%CI
1	ECONOMIC -> SOCIAL	0.982	0.065	14.555	0.872	1.128
2	CUSTOMER -> SOCIAL	1.004	0.059	16.545	0.902	1.133
3	CUSTOMER -> ECONOMIC	0.891	0.064	13.361	0.752	1.011
4	ENVIRONMENT -> ECONOMIC	0.980	0.063	15.144	0.878	1.113
5	ECONOMIC -> SUSTAINABLE LOGISTIC	0.138	0.086	1.025	0.028	0.350
6	CUSTOMER -> SUSTAINABLE LOGISTIC	0.129	0.076	1.334	0.028	0.310
7	ENVIRONMENT -> SUSTAINABLE LOGISTIC	0.129	0.080	0.938	0.030	0.342
8	SOCIAL -> SUSTAINABLE LOGISTIC	0.142	0.077	0.767	0.035	0.316

Source: Processed data (2023).

Figure 5. Sustainable logistic measurement model.

Figure 6. PCA diagram.

Table 7. PCA value

Variable	PCA Value
IT	0.1514
SEGMENT	0.1298
ENVIRONMENT	0.1320
PROFIT	0.1370
HEALTH	0.1245
EMISSION	0.1264
SAFETY	0.1288
EMPLOY	0.1301
FINANCE	0.1266
SERVICE	0.1198
TRAFFIC	0.1144
INFRASTRUCTURE	0.1110

Source : Processed data (2023).

Figure 7. LDA diagram.

Figure 8. Cause loop diagram sustainable logistic.

Figure 9. Sustainable logistic simulation.

Figure 10. Model simulation result.

Table A1. Variables and indicators

Latent Variable	Dimension	Manifest Variable/Indicator
Economic Sustainability	Traffic Congestion Reduction (Reyes-Rubiano et al., 2021) (Lazar et al., 2021),	1. Special attention to the contribution of traffic congestion to pollution (Reyes-Rubiano et al., 2021)
		2. Commitment to minimize travel time (Lazar et al., 2021)
		3. Commitment to minimize delivery times (Lazar et al., 2021)
		4. Efficient distribution of freight transport in urban areas (Salamzadeh et al., 2022)
		5. Approaches to reduce environmental impacts and traffic congestion (Škultéty et al., 2021)
		6. Night delivery schedule to limit freight transport during city rush hours during the day (Dolinayova & Cerna, 2019)
	Profitability Goals (Reyes-Rubiano et al., 2021) (Škultéty et al., 2021)	1. Minimize logistics costs (Reyes-Rubiano et al., 2021)
		2. Vertical (government) and horizontal (stakeholders) cooperation (Reyes-Rubiano et al., 2021)
		3. Responsible consumption and production systems (Lazar et al., 2021)
		4. Efficient urban logistics system (Lazar et al., 2021)
		5. Livable environment around road infrastructure (Škultéty et al., 2021)
		6. Mechanism for managing the use of natural resources (Škultéty et al., 2021)
		7. Mechanisms to prevent negative externality costs (Škultéty et al., 2021)
	Financial Performance (Shi & Yu, 2013) (Lazar et al., 2021), (Rahiminezhad Galankashi & Mokhatab Rafiei, 2022)	1. Efficiency in working capital management and financial performance (Shi & Yu, 2013)
		2. Cost efficiency for the procurement cycle (Sroufe & Gopalakrishna-Remani, 2019)
		3. Efficiency of inventory turnover and cash-to-cash cycles (Rahiminezhad Galankashi & Mokhatab Rafiei, 2022)
		4. Sales growth in the manufacturing cycle (Reyes-Rubiano et al., 2021)
		5. The efficiency of the customer order cycle as measured by the size of the market share and inventory turnover (Lazar et al., 2021)
Environmental Sustainability	Reducing environmental problems (Ubeda et al., 2011) (Reyes-Rubiano et al., 2021), (Škultéty et al., 2021)	1. Introduction of new technology in the form of alternative fueled vehicles (Ubeda et al., 2011)
		2. Minimize the weight of transportation vehicles to minimize fuel/energy consumption (Reyes-Rubiano et al., 2021)
		3. Heterogeneous fleet to increase the load factor (Reyes-Rubiano et al., 2021)
		4. A clear mechanism for calculating average speed and mileage (Škultéty et al., 2021)
		5. A clear mechanism to account for idle-time (Škultéty et al., 2021)
		6. A clear mechanism to reflect different traffic situations (Kumar, 2022)
	Reducing emissions (Reyes-Rubiano et al., 2021) (Škultéty et al., 2021), (Kumar, 2022)	1. Reducing emissions and waste (Reyes-Rubiano et al., 2021)
		2. The use of alternative fuels (Lazar et al., 2021)
		3. Affordable and clean energy (Škultéty et al., 2021)
		4. Product stewardship with the principle of stratification (Kumar, 2022)
		5. The mechanism for reducing the burden on the environment (Kumar, 2022)
		6. Emission test for vehicles (Focus Group Discussion Findings)
	Infrastructure protection (Reyes-Rubiano et al., 2021) (Škultéty et al., 2021),	1. Multimodal transportation system (Reyes-Rubiano et al., 2021)
		2. Energy efficiency in corporate buildings/offices (Reyes-Rubiano et al., 2021)
		3. The integration of electric vehicles supports more effective infrastructure changes (Škultéty et al., 2021)
		4. Battery charging and storage stations(Škultéty et al., 2021)
		5. Environmental management system meeting the criteria (ISO 14,001) (Focus Group Discussion Findings)
Social Sustainability	Health Purposes (Sodhi & Tang, 2018)(León & Juan, 2014), (Reyes-Rubiano et al., 2021) (Salamzadeh et al., 2022),	1. Regulation/commitment to safety, health and labor standards (Sodhi & Tang, 2018)
		2. Regulation/commitment to workload balance (León & Juan, 2014)
		3. Special attention to the health impacts and living conditions of the wider community (Reyes-Rubiano et al., 2021)
		4. Attention/consideration of the welfare of customers and society (Salamzadeh et al., 2022)
	Safety Purposes (Škultéty et al., 2021) (Sodhi & Tang, 2018), (Schaltegger & Burritt, 2014) (Salamzadeh et al., 2022),	1. Regulation/commitment to company costs (Škultéty et al., 2021)
		2. Regulations/commitment to road safety (Sodhi & Tang, 2018)
		3. Procedures for awarding employee salaries and wages (León & Juan, 2014)
		4. Regulations/commitments to city livability (Schaltegger & Burritt, 2014)
		5. Minimal air and noise pollution (Salamzadeh et al., 2022)
	Employment Practices (León & Juan, 2014) (Reyes-Rubiano et al., 2021), (Salamzadeh et al., 2022)	1. Emphasizing discipline and ethics at work (León & Juan, 2014)
		2. Ethical collection transactions (León & Juan, 2014)
		3. Delivery of official goods (Reyes-Rubiano et al., 2021)
		4. Protection for underage workers (Salamzadeh et al., 2022)
		5. Good support to suppliers to increase the effectiveness of logistics transportation performance (Salamzadeh et al., 2022)
Customer Management Sustainability	Service management (Wang et al., 2018)(Wang et al., 2020),	1. Delivery of goods according to the time confirmed by the customer (Wang et al., 2018)
		2. Operational system service standards to meet customer service accuracy (Wang et al., 2018)
		3. Collaborative efforts to accelerate delivery (Wang et al., 2020)
		4. Various delivery options (Wang et al., 2020)
		5. Cheap shipping cost options affordable by the customer (Focus Group Discussion Findings)
		6. Packaging to ensure security during delivery (Focus Group Discussion Findings)
	Use of Information Technology (Nagariya et al., 2022) (Nouri et al., 2019),	1. The information system manages complaints from customers (Nagariya et al., 2022)
		2. The information system speeds up the response time for customers (Nagariya et al., 2022)
		3. The information system provides and updates information and feedback from customers in “real-time” (Nouri et al., 2019)
		4. The information system for identifying potential customers (Nouri et al., 2019)
	Customer segmentation (Nagariya et al., 2020, 2022) (Focus Group Discussion Findings)	1. Customer segmentation (Nagariya et al., 2022)
		2. Products and management for different customer segments (Nagariya et al., 2022)
		3. Different offers based on the customer’s economic value (Focus Group Discussion Findings)

Table A2. Flow diagram symbol and Description

Symbol	Name	Description
	LEVEL	Describes the accumulation of the system
	INFLOW	Describes the rate towards LEVEL
	OUTFLOW	Describes the rate from LEVEL
	AUXILIARY	Explanatory variables

Hosseini-Motlagh, S.-M., Nouri-Harzvili, M., Choi, T.-M., & Ebrahimi, S. (2019). Reverse supply chain systems optimization with dual channel and demand disruptions: Sustainability, CSR investment and pricing coordination. Information Sciences, 503, 606–634. https://doi.org/10.1016/j.ins.2019.07.021

 Web of Science ®Google Scholar

Reyes-Rubiano, L., Serrano-Hernandez, A., Montoya-Torres, J. R., & Faulin, J. (2021). The sustainability dimensions in intelligent urban transportation: A paradigm for smart cities. Sustainability, 13(19), 10653. https://doi.org/10.3390/su131910653

 Web of Science ®Google Scholar

Lazar, S., Klimecka-Tatar, D., & Obrecht, M. (2021). Sustainability orientation and focus in logistics and supply chains. Sustainability, 13(6), 3280. https://doi.org/10.3390/su13063280

 Web of Science ®Google Scholar

Salamzadeh, A., Hadizadeh, M., Rastgoo, N., Rahman, M. M., & Radfard, S. (2022). Sustainability-oriented innovation foresight in international new technology based firms. Sustainability, 14(20), 13501. https://doi.org/10.3390/su142013501

 Web of Science ®Google Scholar

Škultéty, F., Beňová, D., & Gnap, J. (2021). City logistics as an imperative smart city mechanism: Scrutiny of clustered eu27 capitals. Sustainability, 13(7), 3641. https://doi.org/10.3390/su13073641

 Web of Science ®Google Scholar

Dolinayova, A., & Cerna, L. (2019). The possibilities of increasing the economic efficiency of Regional Rail Passenger transport—A case study. Sustainable Rail Transport, 97.

 Google Scholar

Shi, M., & Yu, W. (2013). Supply chain management and financial performance: Literature review and future directions. International Journal of Operations & Production Management, 33(10), 1283–1317. https://doi.org/10.1108/IJOPM-03-2012-0112

 Web of Science ®Google Scholar

Rahiminezhad Galankashi, M., & Mokhatab Rafiei, F. (2022). Financial performance measurement of supply chains: A review. International Journal of Productivity and Performance Management, 71(5), 1674–1707. https://doi.org/10.1108/IJPPM-11-2019-0533

 Web of Science ®Google Scholar

Sroufe, R., & Gopalakrishna-Remani, V. (2019). Management, social sustainability, reputation, and financial performance relationships: An empirical examination of US firms. Organization & Environment, 32(3), 331–362. https://doi.org/10.1177/1086026618756611

 Web of Science ®Google Scholar

Ubeda, S., Arcelus, F. J., & Faulin, J. (2011). Green logistics at Eroski: A case study. International Journal of Production Economics, 131(1), 44–51. https://doi.org/10.1016/j.ijpe.2010.04.041

 Web of Science ®Google Scholar

Kumar, S. (2022). A quest for sustainium (sustainability premium): Review of sustainable bonds. Academy of Accounting & Financial Studies Journal, 26(2), 1–18.

 Google Scholar

Sodhi, M. S., & Tang, C. S. (2018). Corporate social sustainability in supply chains: A thematic analysis of the literature. International Journal of Production Research, 56(1–2), 882–901. https://doi.org/10.1080/00207543.2017.1388934

 Web of Science ®Google Scholar

León, R., & Juan, A. A. (2014). Promoting corporate social responsibility in logistics throughout horizontal cooperation. Managing Global Transitions, 12(1), 79–93.

 Google Scholar

Schaltegger, S., & Burritt, R. (2014). Measuring and managing sustainability performance of supply chains: Review and sustainability supply chain management framework. Supply Chain Management: An International Journal, 19(3). https://doi.org/10.1108/SCM-02-2014-0083

 Web of Science ®Google Scholar

Wang, S., Tao, F., & Shi, Y. (2018). Optimization of location–routing problem for cold chain logistics considering carbon footprint. International Journal of Environmental Research and Public Health, 15(1), 86. https://doi.org/10.3390/ijerph15010086

 PubMed Web of Science ®Google Scholar

Wang, X., Yuen, K. F., Wong, Y. D., & Teo, C.-C. (2020). E-consumer adoption of innovative last-mile logistics services: A comparison of behavioural models. Total Quality Management & Business Excellence, 31(11–12), 1381–1407. https://doi.org/10.1080/14783363.2018.1485484

 Web of Science ®Google Scholar

Nagariya, R., Kumar, D., & Kumar, I. (2022). Sustainable service supply chain management: From a systematic literature review to a conceptual framework for performance evaluation of service only supply chain. Benchmarking: An International Journal, 29(4), 1332–1361. https://doi.org/10.1108/BIJ-01-2021-0040

 Web of Science ®Google Scholar

Nouri, F. A., Nikabadi, M. S., & Olfat, L. (2019). The role of supply chain features in the effectiveness of sustainability practices in the service supply chain: Application of fuzzy rule-based system. International Journal of Information Technology & Decision Making, 18(3), 867–899. https://doi.org/10.1142/S0219622019500111

 Web of Science ®Google Scholar

Nagariya, R., Kumar, D., & Kumar, I. (2020). Service supply chain: From bibliometric analysis to content analysis, current research trends and future research directions. Benchmarking: An International Journal, 28(1), 333–369.

 Web of Science ®Google Scholar

Data availability statement

All data generated or analysed during this study are included in this published article (and its additional files). The ChIP-seq data have been deposited in the repository Politeknik APP database [eprint/3607] (https://repository.poltekapp.ac.id/id/eprint/3607). Requests for material should be made to the corresponding authors.