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Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251241Print ISSN: 2288-4637 / Online ISSN ors Influencing Digital Transformation of LogisticsService Providers: A Case Study in ThailandPutthiwat SINGHDONG1, Kamonchanok SUTHIWARTNARUEPUT2,Pongsa PORNCHAIWISESKUL3Received: January 15, 2021Revised: March 21, 2021 Accepted: April 01, 2021AbstractThis research explores and develops digital transformation factors influencing the logistics service-provider sector in Thailand while alsoexamining the impact sustainability factors associated with digital transformation. Divided into two parts, Part one of the theoretical studyframework covers 21 factors relating to logistics, including drivers, objectives, implications, and success factors. The second part concerns23 factors associated with logistics sustainability, including economic, environmental, and social aspects. This quantitative empiricalresearch was conducted using an online questionnaire instrument, and a structural equation modeling (SEM) technique was used to testthe proposed model. The findings from 545 samples collected between August and November 2020 from respondents working in logisticsservice-provider companies in Thailand show that digital transformation drivers and objectives seem likely to impact success factors andimplications in digital transformation positively. Digital transformation success factors also positively impact logistics sustainability. Incomparison, logistics sustainability has a significant impact on Thailand’s logistics service-provider sector’s economic, environmental, andsocial aspects. Lastly, this research highlights the significance of digital transformation success factors and extends the current knowledgeabout digital transformation factors and their potential impact on logistics sustainability.Keywords: Digital Transformation, Logistics Sustainability, Logistics Service ProvidersJEL Classification Code: M19, O20, O30, Q561. IntroductionThe application of digital technology in the logisticsbusiness shows a growing trend. Businesses across everysector are now adopting digital technologies and reshapingtheir models in line with new digital transformation trends.They come up with new processes or modify the existingFirst Author and Corresponding Author. Ph.D. Candidate, Programin Logistics and Supply Chain Management, Graduate School,Chulalongkorn University, Bangkok, Thailand [Postal Address: 254Phayathai Rd, Pathum Wan, Pathum Wan District, Bangkok 10330,Thailand] Email: [email protected] Professor, Department of Commerce, Chulalongkorn BusinessSchool, Chulalongkorn University, Bangkok, Thailand.Email: [email protected] Associate Professor, Program in Logistics and Supply ChainManagement, Graduate School, Chulalongkorn University, Bangkok,Thailand. Email: [email protected] Copyright: The Author(s)This is an Open Access article distributed under the terms of the Creative Commons AttributionNon-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permitsunrestricted non-commercial use, distribution, and reproduction in any medium, provided theoriginal work is properly cited.ones, build new company cultures, and even introduce brandnew customer experiences to satisfy the changing needs ofconsumers and market demands. Digital transformation inlogistics and transportation helps companies from the sectorto take advantage of new technologies and stay competitivein a market that is continuously expanding. These includethe web, the cloud, sensors, data analytics, machine learning,blockchain technology, and the Internet of Things (IoT),which improve vertical and horizontal alignment aroundsupply chain networks.Representing a revolutionary change in business thinkingand logistics implementation, this digital transformation islikely to create a need for a new business model to producesmarter, more enabled, efficient, and feasible digital logistics.To achieve authentic and real-time information exchangeamong supply chain stakeholders, it is necessary to adoptuseful technologies such as sensor-enabling technology, theIoT, and Cloud-based database systems (Schrauf & Berttram2016) The integration of these technologies with the supplynetwork offers easy access to customer needs by effectivelysharing the tracking information of product or service

242Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251deliveries. This technological integration can typically entailhigh costs with slow diffusion (Korpela et al., 2017).Another goal of business is sustainability. Sustainabledigital logistics will require firms to reconsider their digitalbusiness strategies and reorganize the direction of businessoperations throughout the supply chain towards moresustainability, including balanced, sustainable economic,environmental, and social development, representingcomplex inter-relationships. Digital transformation inlogistics and supply chain management is the changes in valuecreation by the use of digital transformation technologies(DTT), an adaptation of strategies and processes, and theadaptation of enablers such as innovation and leadershipto support the achievement of goals such as an increase inagility, higher productivity, and a more customer-centricsupply chain. The main drivers concerning manufacturers’investment in logistics and supply chain management are toachieve real-time product visibility, faster innovation, andlower cost to serve as well as an improvement in planning(Salam & Hoque, 2019).The latest research suggests that digital transformationin logistics and supply chain management is currentlyevolving, and there is still no clear understanding of itsconcrete implications (Junge et al., 2020). This exploratoryresearch paper intends to provide insights into moresustainable logistics and supply chain management.Specifically, the study aims to identify digital transformationfactors influencing logistics sustainability and examine theimpact of digital transformation on sustainable logistics andlogistics service providers (LSPs) in Thailand.a platform for interactions between external suppliers andconsumers. (Bechtsis et al., 2017).2. Literature Review2.2. Logistics Services Providers (LSPs)2.1. Digital TransformationLSPs play an essential role in the global supply chain bydelivering goods or services from suppliers to customers.Globalization has become a crucial driver in shaping businessstrategies. In the last two decades, leading firms havedeveloped products for the global market while also havingto source components worldwide (Banomyong & Supatn,2011). External trade growth has occurred in both directions,i.e., imports and exports, with newly industrializing countriessuch as Singapore, Malaysia, Thailand, and Indonesiaexperiencing substantially higher growth. Increased worldtrade has resulted in increased demand for logistics services,as well as increased competition in the sector. The Councilof Supply Chain Management Professionals defined LSPs as“Any business which provides logistics services includingthose businesses typically referred to as 3PL, 4PL, LLP, etc.Services may include provisioning, transport, warehousing,packaging, and so on.” (CSCMP, 2013 p. 117). According toMultaharju and Hallikas (2015), third-party logistics (3PLs)are “activities carried out by a logistics service provider onbehalf of a shipper and consisting of at least management andDigital transformation has mainly been associated with theneed to use emerging technologies to maintain viability in theInternet era. Both online and offline services and products aredistributed to the customer (Puriwat & Tripopsakul, 2021). Thetransformation of online services has increased flexibility andautomation by standardization (Andal-Ancion et al., 2003).Digital technology is rapidly developing globally becauseof its widespread availability, portability. More importantly,its capability to transmit information, merchandise, anddistribute content (Lee et al., 2015). According to consumerdemand, some define transformation as a process of updatingbusiness models to use the latest technologies (Berman,2012). The effects of digital transformation strategiesinclude market delivery changes and new types of directcustomer interactions, such as adapting goods and servicesto changing customer needs through social media (Bilgeriet al., 2017). Digitization provides for the development ofnetwork economies, in which the core business model offers2.1.1. Digital Transformation among LSPsDigitization disrupts logistics systems to the degreethat it enables processes to be streamlined or increasesefficiencies. The logistics networks of businesses canbecome more environmentally sustainable using analytics(including hyperconnectivity, supercomputing, and big data).Companies can use technology to save money and contributeto a more efficient and environment-friendly approach.A white paper from the World Economic Forum shows thatthe value of the logistics industry could increase by up toUS 1.5 trillion by 2025 (Weinelt, 2016). Digital logisticscomprises four main elements: technology, operation,organization, and expertise (Stuermer et al., 2011).2.1.2. Factors Involved in Digital TransformationA systematic review of publications on digitizationand related concepts was conducted by Morakanyane et al.(2017), who evaluated 21 research-related contributions,dividing them into three groups, based on which researchmay contribute useful insights: drivers and goals, successfactors, and implications (Osmundsen et al., 2018). Driversand goals are responsible for initiating and affecting digitaltransformation (Morakanyane et al., 2017). Essentialorganizational elements for digital transformation are linkedto success factors. Implications relate to the impacts of anenterprise’s digital change (Morakanyane et al., 2017).

Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251execution of transportation and warehousing (if warehousingis part of the process)” Razzaque and Sheng (1998). described3PLs as “the use of external companies to perform logisticsfunctions which have traditionally been performed within anorganization”. A third-party firm’s responsibilities may includethe entire logistics process or specific tasks within it. The useof LSPs is indisputably linked to business outsourcing in thesame way as a driven model of business competitiveness.2.3. Logistics SustainabilityDigitization facilitates the automation of workflows andaccelerating the production and distribution of documents(Choi et al., 2019). A sustainable digital logistics ecosystemreveals how digitization can impact logistics from asustainable economic, environmental, and social perspective(Monnet & Le Net, 2011) The characteristics of sustainabilitydimensions can be summarised as follows:Economic: An affordable mechanism that works effectively,provides collaborative solutions and a mixture of choices in themode of transport, and benefits the local economy.Environmental: Decreased greenhouse gas emissions,pollution, and waste; minimized non-renewable energy use; andthe use of technologies that reuse and recycle their components.Social: An essential individual/community accesscriterion to be safer and encourage healthier behaviors andequality within and across generations (Kayikci, 2018).Sustainability is especially playing a pivotal role in dealingwith the business’ ascent in terms of speed and change (Fakir& Jusoh, 2020).3.  Conceptual Framework andHypothesis Development243characterized by the collection and analysis of quantitativedata. The experimental research examined all applicablecurrent models and gathered data from previous studieson warehouse activity services and distribution amongThailand’s LSPs, focusing on various factors, including digitaltransformation and logistics sustainability. The results of theliterature review helped to establish the conceptual model.The following research hypotheses were formulatedconcerning the link shown in Figure 1 between digitaltransformation factors and the Sustainability of LSPs inThailand. This research will be useful in explaining issuesrelated to sustainability. The hypotheses proposed, based onthe conceptual model, are described below:H1: The drivers of digital transformation create apositive impact on digital transformation success factors.H2: The objectives of digital transformation have apositive impact on digital transformation success factors.H3: Digital transformation success factors have apositive impact on logistics sustainability.H4: Logistics sustainability has a positive impact on theeconomic impact of logistics sustainability.H5: Logistics sustainability has a positive impact on theenvironmental impact of logistics sustainability.H6: Logistics sustainability has a positive impact on thesocial impact of logistics sustainability.H7: Digital transformation success factors have apositive impact on the implications of digital transformation.4. Research Methodology4.1. Research Design and Data CollectionThe effect of digital transformation factors on thecompetitiveness of LSPs in Thailand is described in thisreport. The research uses a sequential exploratory design,Using an online survey questionnaire, a quantitativemethod was used to examine the research hypotheses andtest the proposed model. SPSS AMOS 20.0, using structuralequation modeling (SEM), was used to analyze and test theFigure 1: A proposed Research Framework

244Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251data. The questionnaire was developed in consultation witha group of logistics experts from business and academia,following a series of interviews. Quantitative data wascollected through the questionnaire survey. The structuredquestionnaire comprised questions on the effects of digitaltransformation factors on the competitiveness of LSPs inThailand. The survey research phase included the generationof hypotheses based on established literature and theory,research design, instrument design, sample design, datacollection, data analysis, and inference making (Bell &Bryman, 2007).4.2. Questionnaire DevelopmentThe research questionnaire was developed based on theinstrument creation methods suggested by Churchill andGilbert (1979) and Haynes (1995), involving three stages.Stage 1 consists of examining studies in the literature review,defining the construct, and producing a sample of factors tooperationalize each construct. Stage 2 involved instrumentdevelopment and data collection. This study used questionsformulated using a Likert scale, which is often used in similarresearch and enables respondents to display a favorable orunfavorable attitude toward the object of interest (Cooper &Schindler, 2006). Pre-testing the instrument involves contentvalidity testing to ensure that standardized procedures areapplied during data collection.The pilot study involved appraising and refining the tooland examining the internal consistency of the factors. Aftera pre-test with eleven industry and academia experts, theresults showed one additional driver of digital transformation,namely technology transfer from foreign countries.Regarding the digital transformation objectives, there weretwo new factors: reducing operational costs and competitiveadvantage. There were also two new digital transformationsuccess factors: leadership vision and information technologyacceptance. Logistics sustainability in terms of the economyand the environment remained the same.In contrast, logistics sustainability in society sawtwo new factors: visibility and social enterprise. Finally,the implications for digital transformation remained atthree factors. The questionnaire was then validated usingindex objective congruence (IOC), and its reliability wastested using Cronbach’s alpha. The IOC, obtained frominterviewing eleven experts in logistics, was more significantthan 0.5. Next, the reliability was tested in a pilot study of30 individuals involved in the logistics industry. In total,Cronbach’s alpha was more significant than 0.7, exceptfor the digital transformation driver construct, a changingcompetitive landscape, which was 0.517.The results revealed a total of 51 factors which, alongwith constructs and measurement scales, are presented inTable 1.Exploratory factor analysis is a statistical techniquethat is used to reduce data to a smaller set of summaryvariables and to explore the underlying theoretical structureof the phenomena. It is used to identify the structure of therelationship between the variable and the respondent. In thisstudy, the inter-relationships among the four dimensions ofdigital transformation and the three dimensions of logisticssustainability were examined using exploratory factor analysis(EFA) to establish the underlying dimensionality of digitaltransformation and logistics sustainability construct. Theresult of KMO value near 1.0 and Bartlett’s Test significancenear 0.00 indicates that the data is adequate and suitable tocontinue the reduction process (Hoque & Awang, 2016). Theoutput shown in Table 2 demonstrates that seven dimensionsor components were obtained using the EFA method, whichsuggests a drop item when the factor loading value is below0.5 (Mvududu & Sink, 2013). Table 2 below summarizesthe EFA output. Overall, the EFA procedure dropped sevenitems under the seven dimensions of digital transformationand logistics sustainability constructs, while 44 items wereconsidered for confirmatory factor analysis (CFA).5. Results5.1. Sample ProfileData was collected through a self-completed onlinequestionnaire distributed to Logistics Service Providers(LSPs) employees in Thailand. To pinpoint the specificresearch areas, we compiled a list of five well-knownLSP associations in Thailand, viz., The Federation ofThai Industries (TILOG), the Thai International FreightForwarders Association (TIFFA), the Thai AirfreightForwarders Association (TAFA), the Thai Logistics andProductions Society (TLAP), and the Thai Transportation &Logistics Association (TLTA). Data from a total of 545 validquestionnaires was used for the data analysis. SPSS statistics25 was used to generate descriptive statistics to analyzerespondents’ demographic characteristics. The primaryservice offered was Transportation service at 33.6%, themost common number of employees was 100 to 500 people(33%), the most frequent length of work experience was 2 to5 years (34.5%), and the most common annual income wasTHB 100–500 million (22%) (Table 3).5.2. Measurement ModelConfirmatory factor analysis was used to assess therelationships between constructs and their retained objects.To estimate the presumed relationships of the variables, atotal goodness-of-fit test was conducted, as well as separatetests for significance. This model contains 44 observablevariables and seven latent variables. Table 4 summarises

Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251245Table 1: Summary of Questionnaire Constructs, Variables, and Results from the Pilot Validity and Reliability s factorsImplicationsfor digitaltransformationLogisticssustainability –economicsNoItemFactor CriteriaIOCCronbach’s Alpha1DV1Customer behavior and expectations0.910.5172DV2Digital shifts in the industry0.823DV3Changing competitive landscape0.914DV4Regulatory changes0.645DV5Technology transfer from foreign countries*0.556OB1Ensure digital readiness0.827OB2Digitally enhance products0.558OB3Embrace product innovation0.649OB4Develop new business models0.7310OB5Improve digital channels0.9111OB6Increase customer satisfaction0.8212OB7Reduce operation costs*0.8213OB8Competitive advantage*0.8214SF1A supportive organizational culture0.8215SF2Well-managed transformation activities0.8216SF3Leverage external and internal knowledge0.8217SF4Engage managers and employees0.6418SF5Grow information system capabilities1.0019SF6Develop dynamic capabilities0.8220SF7Develop a digital business strategy0.9121SF8Align business and information systems0.7322SF9Leadership vision*0.5523SF10Information technology acceptance*0.6424IP1Reforming an organisation’s informationsystem25IP2New business model0.9126IP3Effect outcome and performance0.9127LSE1Logistics costs1.0028LSE2Delivery time0.7329LSE3Transport delays0.5530LSE4Inventory reduction0.5531LSE5Loss/damage0.6432LSE6Frequency of service0.5533LSE7Forecast 0.7336LSE10Transport 905

246Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251Table 1: (Continued)ConstructNoItemFactor CriteriaIOCCronbach’s AlphaLogisticssustainability –environment38LSN1Resource efficiency0.640.87639LSN2Process energy0.5540LSN3Process SN6Land-use impact0.6444LSS1Development 4Safety0.7348LSS5Labor .6451LSS8Social enterprise*0.64Logisticssustainability –society0.913*New Items from Expert.Table 2: Summary of EFA OutputConstructDigital transformation driversNo. of Itemsbefore EFAItems DroppedReason forDroppingNo. of Itemsafter EFA45DV3 changing competitivelandscapeFactor loading 0.5Digital transformation objectives8–Factor loading 0.58Digital transformation successfactors10–Factor loading 0.510Implications for digital transformation3–Factor loading 0.53Logistics sustainability in economics11LSE11 ApplicationFactor loading 0.510Logistics sustainability in theenvironment6LSN1 Resource efficiencyLSN2 Process energyFactor loading 0.54Logistics sustainability in society8LSS3 HealthLSS4 SafetyLSS8 Social enterpriseFactor loading 0.55Total517the items and constructs of our measurement model. TheCronbach’s value, which measures the reliability of the modelvariables, was between 0.745 and 0.922 (Table 4). Eachconstruct and its respective subscales have values greaterthan 0.7, confirming the constructs’ internal consistency.The discriminant and convergent validities of theconstructs were also determined. Three indices were used to44assess concurrent validity: factor loading values should bemore than 0.7, mean extracted variance (AVE) values shouldbe more than 0.5, and composite reliability (CR) valuesshould be more than 0.7, except for the digital transformationdriver construct, the value of AVE is less than 0.5 (0.482);however, validity is still adequate due to composite reliabilitybeing higher than 0.6 (Fornell & Larker, 1981). The degree

Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251247Table 3: Descriptive StatisticsThai-OwnedForeign-OwnedJoint VenturePrimary ServiceNo%No%No%Logistics service provider4117.43828.634Freight forwarder5423.03425.657Warehouse service4519.12720.3Transportation service9540.4342351001,000–2,00021100–500All 5.62714.98014.7Less than 1008034.92216.33821.014025.7More than 4525.612122.2 26930.43121.83721.013725.1 13.67714.1 1006729.01410.11910.810018.3 0.0TotalNumber of EmployeesTotalWork Experience (years)Annual Income (million Thai baht)Totalof factors that helps in distinguishing one construct fromanother is called discriminant validity. The criterion forsufficient discriminant validity is that the square root of AVEfor each construct should be greater than the relation betweenthat construct and another, confirming each construct’sdiscriminant validity. Overall, in the context of divergent andconvergent validity, a satisfactory construct validity level isindicated by test results, implying that the research constructsare a suitable fit for a structural model assessment.5.3. Structural Model and Hypothesis TestingThe hypotheses underlying the proposed research modelwere tested and used to evaluate the structural model. IBM

248Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251Table 4: Summary of the Measurement Model and its ConstructsDimensionDigital transformationdriverDigital transformationobjectivesDigital transformationsuccess factorsImplications for digitaltransformationLogisticssustainability ineconomicsLogisticssustainability inenvironmentNoFactorLoadingt-valueSECronbach’s .78818.8230.05539LSN60.77415.2570.059

Putthiwat SINGHDONG, Kamonchanok SUTHIWARTNARUEPUT, Pongsa PORNCHAIWISESKUL /Journal of Asian Finance, Economics and Business Vol 8 No 5 (2021) 0241–0251249Table 4: nability 79517.8480.056t-valueSECronbach’s AlphaCRAVE0.9130.8650.562Note: AVE: Average Variance Extracted; CR: Composite Reliability; SE: Standard Error.Table 5: Hypothesis TestingHypothesisPathLoadingt-valueResult(H1). DRIV creates a positive impact on DGSFDGSF DRIV0.3055.219Supported(H2). OBJT has a positive impact on DGSFDGSF OBJT0.8639.748Supported(H3). DGSF has a positive impact on LGSTLGST DGSF0.89110.001Supported(H4). LGST has a positive impact on LGSELGSE LGST0.946–(H5). LGST has a positive impact on LGSNLGSN LGST0.82914.410Supported(H6) LGST has a positive impact on LGSSLGSS LGST0.94816.547Supported(H7). DGSF has a positive impact on IMPIMP     DGSF0.8524.148SupportedAmos software (version 22) was used to conduct a pathanalysis for investigating the causal model. This model’sgoodness-of-fit indicators are as follows: Root Mean SquareError of Approximation (RMSEA) 0.052; ComparativeFit Index (CFI) 0.958; Tucker-Lewis Index (TLI) 0.947;Normed Fit Index (NFI) 0.943; Goodness of Fit Index(GFI) 0.916; df 124; Chi-square 313.705; Minimumdiscrepancy per degree of freedom CMIN/df 2.530. Theseindicators met the required cut-off values, suggesting a goodmodel fit. Table 5 summarises the results of hypothesis testingthat indicate the variables’ relationship with significancerelationship.It was revealed by the regression analysis resultsthat perceived DRIV creates a positive impact on DGSF(SE 0.56; β 0.305; p 0.001; supporting H1), while OBJThas a positive impact on DGSF (SE 0.60; β 0.863 p 0.001; supporting H2). DGSF has a positive impact on LGST(SE 0.69; β 0.891 p 0.001; supporting H3). For Hypotheses4, 5, and 6, the SEM results also revealed that LGSE, LGSN,and LGSS have a significant positive influence on logisticssustainability (SE 0.68, 0.63 and 0.88, respectively), with(SE 0.98; β 0.946, 0.829, and 0.948 p 0.001; supportingH4, H5 and H6). Finally, DGSF has a positive impact onIMP (SE 0.98; β 0.852 p 0.001; supporting H7).6. Discussion and ConclusionThe research has explored and confirmed the influenceof digital transformation on the Sustainability of LogisticsService Providers in Thailand. Digitalization and sustainabilitystrategies should become a cornerstone of LSPs’ businesspractices, and firms must employ digital policies to implementtheir sustainability responsibility initiatives. This DGSF canbe an effective way for firms to be sustainable; initiativeslike DRIV need to focus on adapting technology transferfrom foreign countries, and OBJT concentrates on improvingdigital channels. The primary part of DGSF relies on growthin information system capabilities and developing a digitalbusiness strategy to enhance logistics sustainability by payingattention to saving logistics costs. Environment issues needthe initiation of a policy to reduce pollution. And in respectof the Social factor, the corporations have to pay attention tothe company’s development benefits. Previous studies haverevealed that businesses’ success relies on how firms attemptto enhance digital transformation through the sustainabilityof the Logistics business. By adopting digital transformationapproaches that can be viewed as part of a transformationstrategy, companies can i

may contribute useful insights: drivers and goals, success factors, and implications (Osmundsen et al., 2018). Drivers and goals are responsible for initiating and affecting digital transformation (Morakanyane et al., 2017). Essential organizational elements for digit