Transformation into 4PL: The case of local logistics service providers in Vietnam

JOURNAL OF EASTERN EUROPEAN AND CENTRAL ASIAN RESEARCH Vol.10 No.2 (2023) www.ieeca.org/journal 311 TRANSFORMATION INTO 4PL: THE CASE OF LOCAL LOGISTICS SERVICE PROVIDERS IN VIETNAM Trang Truong Diem Le Tomas Bata University in Zlín, Czech Republic Felicita Chromjaková Tomas Bata University in Zlín, Czech Republic Vang Dang Quang Ho Chi Minh City University of Technology and Education, Vietnam ABSTRACT For a few decades, a new model of logistics service providers (LSP) has appeared and played the role of integrating all operations of the supply chain. This model is known as a logistics integrator, or fourth party logistics (4PL). 4PL has emerged as an ideal configuration for enterprises around the world to effectively utilize their resources and obtain cost reduction across the supply chain. With increasing competition among enterprises, customers’ requirements for complicated services, and global supply chain management, the limitations of inbound services from LSPs have become obstacles to their development. As a result, transformation into 4PL is inevitable for LSPs in the global logistics market. This paper aims to analyze the role, characteristics, and benefits of 4PL. A model for transformation into 4PL for local LSPs in Vietnam is constructed to identify impacting factors. The results point out six factors influencing the transformation process, as well as three important capabilities of 4PL. Keywords: logistics; fourth party logistics; transformation; logistics service providers; supply chain DOI: http://dx.doi.org/10.15549/jeecar.v10i2.1018 INTRODUCTION In the late 1900s and early 2000s, there have been dramatic changes in the logistics field which have been considered to be vital to the improvement of firm productivity. These changes consist of the growth of Third Party Logistics (3PL), the emergence of Fourth Party Logistics (4PL), more complicated partnerships, the increase of multimodal transportation of goods, the decrease of logistics costs, and value chain creation (Li et al ., 2003). Markets have, nowadays, become highly competitive and turbulent, and are constantly changing. The logistics industry has undergone a deep transformation for over three decades, due to the pressure of ever-increasing expectations and demands from customers. Firstly, logistics service providers (LSPs) usually intend to hold up their services and sustainably operate as logistics solution providers. In the long run, however, the tendency of the market creates and motivates more chances for logistics enterprises to run as 4PLS with large projects through integrated and coordinated operations (Lieb, 2005). LSPs have therefore been changing their operations and Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 312 strategy to become logistics integrators. Secondly, Bienstock (2002) pointed out that LSPs’ strategic thoughts concerning external information flows are useful to help them retain their places and foster relationships with their customers. According to Cherneva et al. (2015), the business world is significantly impacted by LSPs’ development, making it essential for enterprises, management professionals, and researchers to recognize 4PL’s opportunities and challenges. Thirdly, considering LSPs as natural candidates for merging their operations to a 4PL, Visser et al . (2004) and Hoek (2006) affirmed that the transformation must be started with comprehensive strategies. Furthermore, grasping the importance of logistics performance, which directly affects customers’ evaluation of logistics service providers, is crucial. Finally, supply chain management is considered one of the core elements of successful 4PL. As first mentioned by Oliver and Webber (1982), supply chain management aims to create value for customers through multi-enterprise integration and efficient, cost-effective management of flows. In this empirical research, the factors influencing the transformation into 4PL of local LSPs in Vietnam are investigated. First, a literature review on various definitions of 4PL and constructs in the model was conducted. Then, the PLS-SEM model is applied to identify the constructs affecting local LSPs’ strategic transformation into 4PL. The findings drawn from the study have considerable implications for both academic and practical fields alike. LITERATURE REVIEW Fourth Party Logistics (4PL) 4PL has been definied variously by researchers in different studies. The term 4PL itself was introduced and owned by Accenture Consulting Company (Dollet and Diaz, 2011). Their definition of 4PL is stated as “an integrator that assembles the resources, capabilities, and technology of its organization and other organizations to design, build and run comprehensive supply chain solutions.” Manufacturers and retailers gain remarkable benefits thanks to 4PL’s effective coordination between LSPs and their clients by managing the overall logistics activities. In the late 1990s, Gattorna mentioned the 4PL concept, which was recognized as a combination of various resources, specific capabilities, and technological utilization to assemble and manage comprehensive supply chain solutions. Yao (2010) concluded that 4PL commendably operates an effective, flexible, and reasonable integration of supply chain activities. Papadopoulou et al . (2013) discussed 4PL as an LSP that creates increasing evolution within the supply chain and focuses on innovation attributes. Pavlic Skender et al . (2013) mentioned 4PL as a joint venture between customers and LSPs. There have been many other researchers who have focused on 4PL and its transformation to adapt to the new, challenging logistics market demand, including Li et al . (2003), Visser et al . (2004), Gattorna et al . (2004), the Supply Chain Executive Board (2005), Hoek (2006), Vivaldini et al . (2008), Win (2008), Ji (2008), and Bajec (2009). 4PL operates with the aim of efficiently utilizing all resources, together with the application of information technology (IT) to simultaneously decrease the firm’s backwardness and increase benefits for all connected parties. As such, 4PL creates a competitive advantage in the global logistics market, offering dominant effectiveness in its service provision to clients. Moreover, later studies asserted the importance and preeminent characteristics of 4PL in the role of an effective and flexible integrator throughout the network (Jianming, 2011; Papadopoulou et al ., 2013). Transformation into 4PL In recent years, logistics has been considered a key element by manufacturing and retailing firms to develop systems within their supply chains (Rafele, 2004). LSPs aim to continually provide logistics services and develop into a solution provider; however, logistics transactions in the market have led to a newer tendency for delivered projects to be larger and more complicated. As a result, LSPs have faced a challenge in their operations (Lieb, 2005). There are even higher expectations on the part of customers for the expertized services LSPs provide as they continue to be more professional in all operations. To keep up with survival and development, strategic logistics solutions should be seriously considered from the point of principles and advantages of all resources (Bienstock, 2002). According to Govindan et al. (2016), 4PLs have high capabilities in optimizing Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 313 the network and utilizing multi-resources. Moreover, 4PLs effectively implement their role in integrating firms participating in the supply chain, resulting in companies coordinating with 4PL as a strategic partner. Visser et al . (2004) analyzed the transformation process into 4PL and suggested that LSPs are well prepared for such transitions. Hoek (2006) highlighted several advantages in the transition from LSP to 4PL, as follows: • Enhancing added value services and rejecting low profitable operations. • Enriching relationships with customers and involving efforts in customers’ supply chains. • Serving clients’ expectations and demands based on high utilization of information systems, but low dependence on owned physical assets. METHODOLOGY Research data In this section, we use statistical data from a data collection survey of 414 LSPs in the logistics industry in Vietnam, as stated in Table I. To ensure the reliability and validity of the measurement index, the authors use the reliability analyses of Cronbach’s Alpha and Average Variance Extracted (AVE) using SmartPLS 4 to eliminate variables uninterpretable to the research concept. Table I: Category of survey respondents Field of logistics operations Quantity (firms) Percentage (%) Transportation, forwarding, and warehousing 90 21.74 Transportation and warehousing 81 19.56 Transportation and forwarding 62 14.98 Transportation 60 14.49 Third-Party Logistics providers (3PL) 55 13.29 Forwarding and warehousing 43 10.39 Forwarding 09 2.17 Transportation, forwarding, and shipping agency 09 2.17 Forwarding and shipping agency 05 1.21 Source: Authors’ calculations Sample size The Structural Equation Model (SEM) is used to analyze the relationships between transformation into 4PL and transportation capability, warehouse operations, information technology (IT) application, human resources, logistics services, transportation infrastructure, logistics outsourcing trends, competition in the logistics market, and policies in the logistics industry. This method requires a large number of samples due to its dependence on sample distribution theory (Raykov and Widaman, 1995). However, Hair et al . (1998) affirmed that there are three types of the sample size used in SEM, including small size ≤ 100, medium size 100 – 200, and large size ≥ 200. The sample size of this study is 414, therefore, it meets the sample size requirement for the research. Research gap The number of 4PL service providers is constantly increasing around the world. There have been many research studies conducted separately on 4PL’s role and model, analysis and comparison between 3PL and 4PL, suggestions for the transition from 3PL to 4PL, and model for conflict resolutions on 4PL development. For the logistics industry in Vietnam, there has only been research conducted on strategic development into 3PL for local private logistics companies in Vietnam. Other studies have mainly focused on the potential and prospects of the logistics industry in Vietnam, including studies on the supply chain and logistics of Vietnam in the context of international economic integration, assessing the National logistics system of Vietnam, sustainable development of logistics in Vietnam in the 2020-2025 period, human resource management of logistics in Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 314 Vietnam, and using the optimization algorithm to evaluate and predict the business performance of logistics companies. Nevertheless, there has not been any research on the transformation from LSP to 4PL, especially in the context of local LSPs in Vietnam. Research hypotheses H1: High transportation capability fosters local LSPs’ strategic transformation into 4PL in Vietnam. One of the key elements of logistics service is the transportation capability of LSPs. Park (2011) pointed out that the main elements of competitiveness between companies include human resources, transportation capability, finance, database, and assets. Transportation planning provides the opportunity for firms to maximize cost-effectiveness when it efficiently integrates collaborative partners (Mason et al ., 2007). Logistics operations could provide highquality services when LSPs have advanced transportation systems. Due to the remarkable significance of transportation, the evaluation of the efficiency of transportation modes have been conducted by many scholars, including Smith and Nash (2014), Mandic et al ., (2014), Chakhtoura and Pojani (2016), Rodseth (2017), and Cui and Li (2017a, 2017b, 2017c). H2: Effective warehouse operations have a positive influence on local LSPs’ strategic transformation into 4PL in Vietnam. Warehouse operations are vital in logistics services since warehouse processes perform activities in the supply chain, including material storage, material division, packaging, gathering, and allocating. The study of Kłodawski et al . (2017) showed a literature review on various stochastic models for analyzing warehouse operations and relevant warehouse strategies through research conducted by Le-Duc and Koster (2005). Kłodawski et al . (2017) pointed out that continuous and proper warehouse operations are very important for significantly impacting the whole supply chain. H3: The absolute level of advanced IT application has a positive impact on local LSPs strategic transformation into 4PL in Vietnam. Scholars (Sabherwal and Jeyaraj, 2015; Chaysin et al ., 2016) have also highlighted the role and usefulness of IT applications in distribution, especially where they aim at costeffectiveness, service quality, and small stock. Studies executed by many scholars, including Pinna et al . (2010), Evangelista et al . (2012), Ghobakhloo and Hong (2014), and Wong et al . (2016), pointed out the enhancement of logistics performance based on IT utilization. According to Sauvage (2003), IT investment would lead large LSPs to achieve superior advantages and become leaders in the global logistics market. H4: High-qualified human resources create a positive influence on local LSPs’ strategic transformation into 4PL in Vietnam. A skilled workforce is essential for running a stable and complicated logistics system. Benefits gained from human resource performance including recruiting, training, and assessment, all of which help firms improve the effectiveness of the whole supply chain and enhance competitive advantages (Hall et al ., 2013). Okeudo (2012), through data collected from LSPs, concluded that LSPs will improve their performance if there is an increase in investment in human resources. Kam et al . (2010) studied the relationship between human performance and logistics capabilities and pointed out that benefits and performance management mechanisms increase the commitment and capabilities to LSPs. H5: Advanced logistics services have a positive impact on local LSPs’ strategic transformation into 4PL in Vietnam. Mangan et al . (2008) stated that “Logistics involves getting, in the right way, the right product, in the right quantity and right quality, in the right place at the right time, for the right customer at the right cost.” In line with this concept, logistics services consist of five main components: IT, stock, transportation, warehousing, and packaging. These activities start with suppliers and end with customers. Logistics services are designed by LSPs to ensure that clients are served with the lowest costs and highest efficiency (Badenhorst-Weiss & Waugh, 2014). Offers in logistics services that are delivered by LSPs have improved to the point of advanced service provision with complex valueadded transport and warehousing activities (Selviaridis and Spring, 2007). H6: Good transportation infrastructure fosters local LSPs’ strategic transformation into 4PL in Vietnam. Fechner (2011) stated that transportation infrastructure, consisting of land, harbor, and Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 315 airway systems, as well as information and communication technology (ICT), have high significance in the logistics service industry. The linear logistics infrastructure of nodes in transportation effectively supports LSPs in providing logistics activities, including packaging, warehousing, delivery, and transshipment. Logistics performance, costeffectiveness, and quality assurance would be enhanced when there is a well-invested transportation system, creating a remarkable advantage for LSPs not only in operation efficiency, but also in their position in the logistics network. H7: The growth of the logistics outsourcing trend creates a positive impact on local LSPs’ strategic transformation into 4PL in Vietnam. The growth of logistics outsourcing has affirmed a powerful trend in the global market. Solakiv et al . (2013) pointed out that financial savings, resourcefulness, and comprehensive operations are core factors for companies in using logistics outsourcing. Outsourcing is considered one of the vital strategies for an enterprise’s business to take advantage of outside resources for non-core activities and to focus on strategic functions for long-term development. Other scholars have stated that logistics outsourcing creates chances for enterprises to achieve their aims, such as costeffectiveness, production enhancement, resourcefulness, and business growth (Aimi, 2007; Bardhan et al., 2006; Lau and Zhang, 2006). H8: The increase of competition in the logistics market causes a positive influence on local LSPs’ strategic transformation into 4PL in Vietnam. Recently, LSPs, under the requirements of economic globalization, have focused on enhancing their capabilities in order to gain their clients’ satisfaction. The survival and growth of LSPs depend on the successful utilization of their capabilities and core resources (Lu & C.S, 2007). As a result, the establishment of a development strategy has been recognized to be significant to LSPs in an increasingly competitive market. According to the 2017 report on logistics in Vietnam, issued by The Ministry of Industry and Trade of the Socialist Republic of Vietnam, competition in the global logistics market has become more fierce. Large logistics service providers throughout the world hold around 15% of the global logistics market share. H9: Completed government policies in the logistics industry create positive stimulation to local LSPs’ strategic transformation into 4PL in Vietnam. The mechanism and policies for logistics industry development have a vital significance for LSPs. According to research conducted by Jin (2012) and Liu et al . (2013), there are two levels of development policies for the logistics industry, consisting of nation and region. National logistics policies are issued to encourage the development of the macroeconomy, while regional logistics policies mainly focus on the specific characteristics of different regions. Scales of measurement In the present study, scales of measurement are established for 10 constructs, with a total of 31 indicators. All indicators are measured on a five-point Likert scale (1 = Very high, 2 = High, 3 = Medium, 4 = Low, 5 = Very low). The specific constructs and indicators are as follows: Table 2: Research constructs and indicators Constructs Indicators Transportation capability (TRA) TRA1: Owned means of transportation TRA2: Speed of transportation nationally and internationally TRA3: Connection of transportation chain and logistics services Warehouse operations (WOP) WOP1: Scale of owned warehouse WOP2: Technology application WOP3: Rate of errors WOP4: Cross-docking utilization Advanced IT application (ITA) ITA1: Highly qualified IT human resources Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 316 Constructs Indicators ITA2: Advanced IT infrastructure ITA3: Strong partnering relationship between IT and logistics service management Human resources (HMR) HMR1: Specialized competence HMR2: Planning and controlling capability HMR3: Learning and integrating competence Logistics services (LOS) LOS1: Provision of diversification and strategy customization of logistics services LOS2: Provision of value-added services to customers LOS3: Logistics service costs Transportation infrastructure (INF) INF1: Airport infrastructure INF2: Harbour infrastructure INF3: Land infrastructure The growth of logistics outsourcing trend (OUT) OUT1: Trend of logistics outsourcing OUT2: Size of an organization adopting logistics outsourcing OUT3: Levels of logistics outsourcing Competition in the logistics industry (COM) COM1: Number of rivals who are LSPs in the logistics market COM2: Market share of LSPs in the logistics market COM3: Types of rivals’ logistics service provision: 2PL, 3PL, 4PL Policies in the logistics industry (POL) POL1: Policies in the logistics industry POL2: Supported policies for LSPs POL3: Directions and strategies of government for the development of the logistics industry Transformation into 4PL (4PL) 4PL1: Value chain creation 4PL2: Integration of multiple 3PL providers’ activities 4PL3: Management competence in global supply chain Source: Authors’ study RESULTS AND DISCUSSION First, the reliability of the research model was assessed. Known as the coefficient determination, the R-Squared formula defines the degree to which the variance in the dependent variable can be explained by independent variables. From the results of bootstrapping, the R-Square of the model is 0.644, and the R-Square Adjusted is 0.636 (as shown in Figure 1). This means that 63,6% of the variation in the dependent variable (4PL) is explained by independent variables (TRA, ITA, HRM, LOS, COM, OUT, WOP, INF, and POL). With this result, the reliability of the research model is demonstrated. Table 2: Continued Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 317 Figure 1: Model of transformation into 4PL Source: Author’s estimations from SmartPLS Based on the recommendations of PLS-SEM theory and the literature of Hair et al. (2017), the constructs’ reliability levels are evaluated using Dijkstra-Henseler’s rho, along with Cronbach’s alpha, coefficients. As shown in Table III, all values exceed the threshold of 0.5 and indicate strong coefficients of the construct’s reliability, as suggested by Bagozzi & Yi (1998) and Hair et al. (2019). Table 3: Construct Reliability and Validity Construct Cronbach's alpha(α) Dijkstra-Henseler's rho_A Composite Reliability Average variance extracted (AVE) COM 0,886 0,891 0,930 0,816 HRM 0,878 0,887 0,925 0,806 ITA 0,896 0,909 0,936 0,829 OUT 0,713 0,717 0,839 0,634 LOS 0,894 0,912 0,934 0,825 POL 0,872 0,891 0,921 0,795 4PL 0,767 0,768 0,866 0,683 TRA 0,715 0,805 0,847 0,662 INF 0,864 0,875 0,916 0,785 WOP 0,907 0,920 0,935 0,783 Source: Author’s estimations from SmartPLS Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 318 The Standardized Root Mean Square Residual (SRMR) value was also considered in order to measure the appropriate level of the model for the research context. According to Hu and Bentler (1999), the SRMR value must be lower than 0.08 or 0.1. Moreover, Henseler et al . (2014) also affirmed that the SRMR value determines “goodness of fit” in PLS-SEM. This value is measured to avoid model misspecification. Table IV shows the SRMR value of the research model as 0.049, again demonstrating the appropriateness of the model. Table 4: Standardized Root Mean Square Residual (SRMR) Original sample (O) Sample mean (M) 95% 99% Saturated Model 0.049 0.034 0.037 0.038 Estimated Model 0.049 0.034 0.037 0.038 Source: Author’s estimations from SmartPLS Regarding indicator loadings of latent constructs, the reliability of indicators must gain outer loadings higher or equal to the threshold of 0.5 to meet the standard of reliability, while composite reliability must be higher or equal to 0.7 (Hulland, 1999). All items in the model are loaded meaningfully and satisfactorily to their corresponding constructs. Values are presented in Table 5. Convergent Validity is used to evaluate the stability of scales. Fornell and Larcker (1981) pointed out that Average Variance Extracted (AVE) must be higher or equal to 0.5 to indicate satisfactory convergent validity. The constructs in the study have minimum to maximum values from 0.634 to 0.829. Therefore, these values are satisfactory. The details are stated in Table 5. Table 5: Indicators’ Outer Loadings, Constructs’ Composite Reliability, and Average Variance Extracted (AVE) Construct Indicator Outer Loadings Composite Reliability Average Variance Extracted (AVE) 4PL 4PL1 0.801 0.866 0.683 4PL2 0.833 4PL3 0.843 COM COM1 0.953 0.930 0.816 COM2 0.871 COM3 0.884 HRM HMR1 0.950 0.925 0.806 HMR2 0.861 HMR3 0.879 INF INF1 0.865 0.916 0.785 INF2 0.909 INF3 0.884 ITA ITA1 0.958 0.936 0.829 ITA2 0.883 ITA3 0.889 LOS LOS1 0.960 0.934 0.825 LOS2 0.870 LOS3 0.893 OUT OUT1 0.799 0.839 0.634 OUT2 0.826 OUT3 0.763 POL POL1 0.857 0.921 0.795 POL2 0.926 POL3 0.891 TRA TRA1 0.929 0.847 0.662 TRA2 0.511 TRA3 0.928 WOP WOP1 0.940 0.935 0.783 WOP2 0.857 WOP3 0.850 WOP4 0.890 Source: Author’s estimations from SmartPLS Transformation into 4PL: The case of local logistics service providers… Trang Truong Diem Le et al. www.ieeca.org/journal 319 A Discriminant Validity assessment aims to ensure that a reflective construct has the strongest relationships with its indicators in the PLS path model (Hair et at., 2017), wherein the square root of AVE must be higher than the Latent Variable Correlations. The square roots of the AVE of the research constructs are shown in bold diagonals in Table 6. Table 6: Discriminant Validity Construct COM HMR ITA OUT LOS POL 4PL TRA INF WOP COM 0.903 INF 0.110 0.886 POL 0.124 0.219 0.892 OUT 0.177 0.130 0.111 0.796 LOS 0.074 0.282 0.201 0.114 0.908 ITA 0.152 0.283 0.271 0.206 0.311 0.911 4PL 0.421 0.332 0.275 0.426 0.444 0.600 0.826 TRA 0.184 0.362 0.268 0.206 0.410 0.324 0.460 0.814 HMR 0.233 0.072 0.233 0.242 0.052 0.106 0.340 0.115 0.898 WOP 0.194 0.371 0.249 0.169 0.385 0.262 0.381 0.538 0.204 0.885 Source: Author’s estimations from SmartPLS To evaluate whether there are relationships between constructs, the Structural Equation Model is used. When the t-value is higher than 1.96, it means that the significant level is lower than 5% (p-value < 0.05). Outer Weights are criteria showing the relative contribution of each indicator. In the Structural Equation Model (SEM), Outer Weights are often lower than Outer Loadings (Hair et al., 2014). To evaluate whether indicators contribute to the establishment of latent variables, bootstrapping should be used. In this study, the software SmartPLS 4 was used to build a Structural Equation Model with 5,000 bootstrap samples. After completing the establishment of the research model, implementing the assessment of the model is essential. There are various ways to evaluate the reliability of the research model. First, the sample may be divided into two subsamples, with one used for building the research model and the remaining used to reevaluate the reliability of that research model. The reliability of the model may also be assessed by collecting more samples. Anderson and Gerbing (1988), however, stated that SEM requires a large number of samples and consumes exorbitant time and costs for researchers. Schumaker and Lomax (2016) then assumed that bootstrapping is appropriate to apply due to its repeated sample method, while the initial samples remain to be major parts. The bootstrapping method uses the obtained sample data from the study to resample it various times to create many simulated samples. The sampling distributions are considered the foundation for confidence intervals and hypothesis testing, with the t-value calculated based on the distributions of created samples. Table 7: Path Coefficient and Construct Relationships Effect Bootstrapping results Empirical remarks Original Coefficient Mean value Standard deviation t-value p-value COM -> 4PL 0,244 0,245 0,033 7,345 0,000 Supported HRM -> 4PL 0,165 0,165 0,032 5,082 0,000 Supported ITA -> 4PL 0,384 0,383 0,032 11,912 0,000 Supported OUT -> 4PL 0,208 0,209 0,035 6,022 0,000 Supported LOS -> 4PL 0,208 0,208 0,039 5,352 0,000 Supported TRA -> 4PL 0,127 0,127 0,040 3,137 0,002 Supported POL -> 4PL -0,009 -0,008 0,031 0,282 0,778 Not supported INF -> 4PL 0,056 0,056 0,034 1,640 0,101 Not supported WOP -> 4PL -0,002 -0,002 0,038 0,054 0,957 Not supported