An Analysis of the Influencing Factors of the End of City Logistics Distribution on the Base of Interpretive Structural Model

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1 Internatonal Journal of Busness and Management Vol. 11, No ISSN E-ISSN Publshed by Canadan Center of Scence and Educaton An Analyss of the Influencng Factors of the End of Cty Logstcs Dstrbuton on the Base of Interpretve Structural Model Xny Dong 1, Hongme Ju 1 & Sfan Yn 1 1 School of Informaton, Bejng Wuz Unversty, Chna Correspondence: Ju Hongme, School of Informaton, Bejng Wuz Unversty, Chna. E-mal: @163.com Receved: Aprl 8, 2016 Accepted: May 18, 2016 Onlne Publshed: June 18, 2016 do: /jbm.v11n7p163 URL: Abstract E-commerce has a rapd development wth the advent of the Internet era, the era of Internet + also let many ndustres to fnd new opportuntes. Now onlne shoppng has become a manstream to meet the needs of people s lfe, especally n the developed ctes, more and more people are wllng to buy all sorts of goods n e - Bay, Amazon, Sunnng, JD and other large e-commerce enterprses. Busness enterprse needs to delver ntact goods quckly to customers to mprove customers ntenton of purchasng. So the development of e-commerce and express ndustry s closely lnked. The end of the cty logstcs needs to contact wth consumers drectly as the last part of the whole process n normal logstcs dstrbuton, whch may occur some problems about the damage of goods, slow nformaton feedback, servce qualty and other ssues wll reduce the satsfacton of consumers and affect reputaton of companes. Ths artcle use ISM technology to analyze the nfluencng factors of the logstcs of the ecommerce enterprse from the perspectve of consumers, and dvde all of the factors nto three levels, each level contans dfferent meanngs whch make a reference for the trend of development of the end of cty logstcs dstrbuton. Keywords: ISM, cty logstcs, nfluencng factors 1. Introducton In the era of bg data, there are huge commercal values behnd the data accumulated n the end of cty logstcs. Snce the end of the logstcs dstrbuton data drectly from the consumer, makng these data become an mportant busness ndcator n the consumer segment, product segmentaton, channel segmentaton, etc, (L, 2014) whch s very mportant for the front end market forecast, customer satsfacton and supply chan management optmzaton. The end of cty logstcs dstrbuton servce dffers from the man logstcs, t does not look at long dstance, large quanttes of quanttes, form neat cargo transportaton, and on the contrary, t s used to solve dfferent varetes and demand of ntegrated logstcs servces n the local geographcal areas for users. Rght now, the basc dea of "Customers Frst" has become a corporate culture n many logstcs companes and reflected n the varous logstcs actvtes. So the research and analyss of the nfluence factors of the termnal logstcs of e-commerce can help the busness enterprse to make the correct decson drecton through these factors, thus to obtan more customer groups. As for the patterns, the end of cty logstcs dstrbuton can be dvded nto three types n Chna. (Ca, 2014). (1) Jont dstrbuton mode. A number of logstcs enterprses band together to make concentrate area dstrbuton for many users, whch can save socal resources by focusng on centralzed advantage greatly. At present, Germany, Japan, Monaco and the countres of the enterprses obtan the very good returns n ths way. (2) Convenence store cooperaton model. Enterprses set up self-servce depost and form logstcs cooperaton wth convenence stores. A lot of enterprses of the Unted States, Brtan and other countres use ths way to apply to ther own logstcs systems. (3) Self settng logstcs center mode. Enterprses do not rely on other nsttutons, but establshng extensve logstcs centers. The typcal representatve of ths model s the Amazon Co, t has been establshed nearly 100 large logstcs centers n the Unted States, coverng the major densely populated ctes n U.S and ensurng the tmely delvery, whch allows 31% of U.S. users can receve the goods n the same day. At present, many Chnese e-commerce enterprses pay lttle attenton to the end of the logstcs dstrbuton, and 163

2 there are many factors that affect the dstrbuton n dfferent degrees. It has been a worthy topc to fnd out the key factor. Commodty delvery has become the bottleneck of goods sales n many large and medum-szed ctes n Chna. (Lan & Wang, 2011) There are also many scholars have a lot of orgnal research on the end of cty logstcs of ecommerce n Chna. Junsheng He and Hao Sh (He & Sh, 2013) ponted out the mportance of delvery speed, and use the genetc algorthm to make a dstrbuton path optmzaton model Nng Le (Le, The dffcultes and countermeasures of the end of E-commerce logstcs, 2014) ponted out that the current plght and causes of Chna e-commerce logstcs termnal faced, and respectvely puts forward the countermeasures of the end of cty and countrysde logstcs Ybo Lu (Lu, 2016) uses the analytc herarchy process to desgn the last klometer logstcs rsk ndex system from dfferent dmensons, and ponts out that the envronmental rsk s the key to the rsk of termnal dstrbuton logstcs Professor Boxong Lan (Lan & Wang, 2011) ponts out that there are three characterstcs at the end of the cty logstcs servce system n Chna: (1) Enterprse vrtualzaton. Some relevant enterprses are n dynamc allance. (2) The scale of resource. Ecommerce enterprses attract a large number of decentralzed logstcs Servce Corporaton to jon, and realze large-scale expanson. (3) Unfed dspatch. Enterprses provde a package of servces for end users. There are many nterlockng nfluencng factors that affect the end of cty logstcs dstrbuton, (Chen, 2013) and these factors have complex relatons wth each other, some maybe the dstrbuton speed or the atttude. (Le, The dffcultes and countermeasures of the end of E-commerce logstcs, 2014) As these complex relatons affect the end of the logstcs dstrbuton, we need to fnd these constrants from the customer's pont of vew and adjust the future drecton of the development of cty logstcs. So ths paper frstly ntroduces the ISM model, whch can solve the problem of the qualtatve analyss. Then through the collecton and analyss of the actual lterature, we fnd out 14 factors nfluencng the end of logstcs dstrbuton, at last usng the ISM technology to draw the progressve relatonshp dagram, and explan the relatonshp between factors and fnd out the deep-level factors. 2. The Theory of ISM Technology 2.1 The Introducton of ISM Technology ISM (nterpretve structural model, referred to as ISM ) s developed by J. Whte Felter professor n 1973, whch s used to analyze the problem related wth the complex socal economcal system, whose feature s to decompose the complex system nto some subsystems, usng people s practcal experence and knowledge, and construct the system of a mult-lever progressve structure model wth the help of computer n the end. The ISM model s an effectve structure analyss method manly based on qualtatve analyss, whch belongs to the concept model, usng a clear chart mage to express the concept of the elements n one system. ISM belongs to the conceptual model, t can put the vague deas and vews nto ntutve model and the applcaton s very extensve. Internatonal problem such as energy ssues and regonal economc development, the scope of enterprses, even ndvdual problems can apply ISM technology to buld structure model. It s partcularly suted to multvarable, complcated, unclear system and mult-project sequencng. The ISM model s appled to the connecton dagram to descrbe the relatonshp between system element, t generally has the followng basc characterstcs: (1) The structure of the system. Nodes are used to represent the elements of system, drected edge of relatonshps between elements. The relatonshp analyss dfferent problem wth dfferent systems, whch can be understood as mpact, depends on, before, need, cause or other meanngs. (2) ISM model s a predomnantly qualtatve analyss model. Ths model can analyze the ratonalty of selectng the elements of the system, and also analyze the relatonshp between elements and the mpact on the overall system. (3) The ISM model can be descrbed n the form of a drected graph and a matrx. The matrx can be processed by the mathematcal method of logcal calculus. If we want to further study the relatonshp between the elements, we can combne the qualtatve analyss and quanttatve analyss through the calculus of matrx form, whch makes the use of the ISM model be more extensve. (4) The ISM model as a form of descrpton of the system, just n the feld of natural scence and socal scence. It s sutable for deal wth problems n complex system of socal scences and smple problems n the system wth natural scence as ts object. 164

3 When developng or modfyng a system, the frst thng we need to know s relatonshp between elements of the system, f s the drect or ndrect relatons, then we can complete the task of development or reconstructon better. In ths paper, we use ISM technology to analyss the nfluencng factors of the end of cty logstcs, and fnd out the relatons between these factors. 2.2 The General Procedures of ISM Workng There are manly seven steps when usng ISM technology: (1) Organze workng group. The numbers of members n a team are generally about 10, and team members should mantan a carng atttude for the problem to be solved. To be able to ensure that people wth dfferent vews nto the team. Informaton should be suffcent, communcaton should be smooth. (2) Set problem. Durng the preparaton phase, the ssue of the set must be consstent, and n the form of text to make the provsons. Members put forward the cause and reason respectvely and sum up 10 to 30 factors s advsable. (3) Choose elements. Specfc the relatonshp between the elements, and usng the arrow lne to connect wth each other. (4) Name the system objectves and elements n a concse and precse language. (5) Structure a model dagram. (6) Make a group dscusson. If the relatonshp between the elements and elements of the composton of the problem are both to be satsfed, then turn to the last step, or turn to the second step. (7) Establsh adjacency matrx and reachable matrx, computng, classfcaton. 3. Establshment ISM of Influencng Factors of the End of Cty Logstcs Dstrbuton 3.1 Choose Key Factors of the End of Cty Logstcs Dstrbuton Based on nvestgaton and a lot of papers about logstcs barrers and dscusson, we fnd 14 factors that affect satsfacton of customers about endng logstcs. The research group draws a total of 14 key factors, then code factors respectvely: S1, S2,..., S 14 (seen n Table 1). Table 1. Key factors of the end of cty logstcs dstrbuton S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 S 13 S 14 Brand reputaton of logstcs enterprses Locaton of dstrbuton center Informaton update and feedback Effcency of courer delvery Courer personnel servce atttude E-commerce enterprses promotonal actvtes Labor costs cty sze and urban populaton Dstrbuton of nfrastructures Locaton of collecton and delvery Coverage of dstrbuton Types of vehcles Delvery schedule The damage rate 3.2 Establshng Adjacency Matrx In the whole system of logstcs, these 14 factors are connected together, and each factor has the nfluence of each other. Adjacency matrx s used to descrbe the relatonshp between the system elements. The element of adjacency matrx can be expressed as follow: a j 165

4 1, S RS S has a drect mpact on the element S j j a= j 0, S RS j S has no drect mpact on the element S j Adjacency matrx descrbes the degree of access between two elements after the path of length 1.The element S S aj 1of adjacency matrx on behalf of has a drect mpact on the element j. For example, a12 1 on behalf of the locaton dstrbuton center has a drect mpact on the effcency of courer delvery. Accordng to the bnary assocatons of elements n the system, the adjacency matrx can be descrbed as follow: (1) S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S S S S S S S A S S S S S S S Fgure 1. Adjacency matrx 3.3 Constructng Reachable Matrx Reachable matrx descrbes the degree of access between elements after a certan length of path n a connecton dagram. If S accesses Sk drectly after length 1, and S k accesses S drectly after length 1, then j S defntely accesses S j after length 2. We can get the reachable matrx by summng up adjacency matrx A and unt matrx I and usng rules of Boolean algebra for operaton. In ths case, we defne matrx M A I, and do exponentatons to M by rules of Boolean algebra for operaton. In the end, we get the reachable matrx R after four teratons. S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S S S S S S S R S S S S S S S Fgure 2. Reachable matrx R 166

5 3.4 Connected Doman Dvson Accordng to the reachable matrx R we can obtan reachable sets R( S ), antecedent sets A ( S ) and Common set R S ) A( S ) as follows: ( Table 2. Frst-class reachable set and antecedent set Element R S ) A S ) R S ) A( S ) ( 1 1 1,2,3,4,5,6,8,9,12,13, ,2,3,4,,7,8,12,13, ,3,4,7,14 2,3,6, ,4,7,14 2,3,4,5,6,8,9,12, ,4,5,7, ,3,4,6,7, ,3,4,5,6,7,8,9,12, ,4,7,8,12,13,14 2,8, ,3,4,7,8,912,13, ,4,7,8,12,13,14 2,8, ,4,7,8,12,13,14 2,8, ,4,7,12,13,14 2,8,9, ,4,7,13,14 2,8,9,12, ,14 2,3,4,5,6,7,8,9,12,13,14 14 ( ( Accordng to the Table 2, frstly fnd the elements n a common set whch can meet the formula A S ) R( S ) A( S ) : ( T { S, S, S, S } (2) Then fnd out the other elements wth the same part of the former elements. If S and S are n the same set j and meet the formula R ( S ) R( S ), ther reachable sets have a common unt, otherwse, they belong to two dfferent connected domans. We can fnd out S, 2 S, 5 S, S are n a same connected doman Herarchcal Dvson In a multstage structure, the reachable set of the hghest level elements can only be composed by tself or the strong connecton elements. If S belongs to the hghest level, t must meet the formula R( S ) ( ) ( ) R S A S, we can obtan factors sets of hghest level as L( S ).Accordng to Table 2 the frst-level: L1 { S1, S7}. After fndng out L 1 { S 1, S 7 }, delete correspondng rows and columns from reachable matrx, get the Table 3, then contnue searchng for new LS ( ) from the remanng reachable matrx tll fnd out no L( S ) from each level. Table 3. Second-class reachable set and antecedent set Elements ( S ) R A S ) R S ) A( S ) 2 2,3,4,,8,12,13, ,4,14 2,3,6, ,14 2,3,4,5,6,8,9,12, ,5, ,4,6, ,8,12,13,14 2,8, ,4,8,912,13, ( ( 167

6 10 4,8,12,13,14 2,8, ,8,12,13,14 2,8, ,12,13,14 2,8,9, ,13,14 2,8,9,12, ,3,4,5,6,7,8,9,12,13,14 14 All the hghest level sets founded from each level consttute { L( S)} { L1, L2,..., Lk}, then usng the same method to seek out a total of 7 levels of elements: L { S, S } L { S } L { S } L { S, S, S } L { S, S } L { S, S, S } L { S, S } Generatng Reduced Reachable Matrx Elements n the same level and the same regon can be accessed to each other s called the strongly connected blocks, whch may exst n each level after the herarchcal dvson. For example, there are sets wth strongly connected blocks such as{ S8, S10, S11} exst n Fg.3. All elements strongly connected blocks contact wth each other among R and then consttute a loop, whch can be selected as a representatve. In ths way, we can pck S to represent the rest elements, and keep elements 8 S1, S2, S3, S4, S5, S6, S7, S8, S9, S12, S13, S to smplfy reachable matrx R. After orderng and sortng, we can get the 14 reduced reachable matrx R : S1 S7 S14 S4 S3 S5 S13 S6 S12 S8 S2 S9 S S S S S S R ' S S S S S S Fgure 3. Reduced reachable matrx R` 3.7 Establshng Herarchcal Structure Model Accordng to the concluson from Fgure 3, we can map drectonal herarchy graph, and get the herarchcal structure model of the nfluencng factors of the end of cty logstcs dstrbuton (seen n Fgure 4). The man purpose of establshng herarchcal model n ths paper s to better understand the progressve relatonshp between factors n one system. We can see that the all the factors are dvded nto three levels accordng to ther nfluence degree on end of cty logstcs dstrbuton: Surface-level factors, mddle-level factors and deep-level factors. 168

7 Fgure 4. ISM model The Surface-level factors nclude brand reputaton of logstcs enterprses, labor costs, damage rate. The Surface factors are manly amed at the "hardware" requrements of logstcs enterprses. When the cty sze s establshed, enterprses should choose sutable dstrbuton scheme to apply to dfferent scales of ctes. For example, n the crowded frst-ter ctes, logstcs and dstrbuton form of the use s storage cabnets. As for some sparsely populated areas, we can choose the approprate traffc tools to ncrease the scope of dstrbuton and reduce transportaton costs. The mddle-level nclude effcency of courer delvery, nformaton update and feedback, courer personnel servce atttude, delvery schedule, e-commerce enterprses promotonal actvtes, types of vehcles. These factors tend to be more software requrements, emphaszng the comprehensve qualty of express delvery personnel and tmely nformaton. When t comes to e-commerce enterprses held more sales promoton actvtes, such as Chnese double eleven actvtes, t wll test the logstcs operaton ablty of many logstc companes. If there are good courer servce, reasonable tme arrangement and effcent delvery and tmely delver the goods, whch can greatly ncrease the customers satsfacton and future transactons of busness and logstcs enterprses. These factors affect the end of cty logstcs dstrbuton from the emotonal pont of vew. The deep-level factors nclude cty sze and urban populaton, locaton of collecton and delvery, coverage of dstrbuton, locaton of dstrbuton center, nfrastructures. Ths s the man source of control at the development of the logstcs ndustry. When customers go shoppng from the Internet, the frst thng they are concerned s f goods are ntact. If e-commerce companes can cooperate wth the hgh reputaton logstcs enterprses, whch wll gve consumers a good sense of securty and mprove consumer purchasng ntenton. Labor costs of servces are the most mportant aspects of the busness or logstcs enterprses, whch affect the delvery scope, personnel servce and delvery effcency to a certan extent, thereby affectng the fnal customer experence. 169

8 Among the three categores, deep-level factors play the most mportant role n the agrcultural logstcs dstrbuton center locaton, mddle-level factors play less role, and surface-level factors play the least role. 4. Concluson In vew of the above factors n three levels of the end of cty logstcs dstrbuton, we can proceed from the followng aspects to optmze the dstrbuton of the end of the logstcs: (1)Besdes the e-commerce enterprses have ther own logstcs system, the logstcs partner of the e-commerce enterprse should choose the enterprse wth hgh reputaton, and establsh the supervson mechansm of the logstcs evaluaton. Lke Chna's enterprses, JD and sunnng, and Amerca's enterprses, lke e-bay, Amazon, they both do successfully and have a lot of hgh-qualty customer sources. (2)Enterprses should choose the hgh qualty packagng whch could reduce the damage to a mnmum, reduce volence dstrbuton frequency n the process of sortng, crculaton and sendng peces, arrange the delvery tme to compress travelng tme. (3)Logstcs enterprses should allocate human resources effcently, and mprove the overall qualty of staff, reduce the cost of labor servces. (4)The current stuaton s there are a huge number of Chnese rural areas, and Chna s rural purchasng potental s huge. The data show that the onlne shoppng turnover reached 353 bllon yuan n Chnese rural area n 2015, an ncrease of 96%. At present, agrcultural product retal sales n network has been up to bllon yuan, Internet users n rural areas reached 5659 mllon people, the new shop reached 118 mllon, t has bult 250 thousand electrc vllage servce statons n the 1000 countes around the whole country. (Zhu, 2012) Although the "Internet + rural" mode s just lke a very attractve cake, now the queston s how to export. Home delvery servce s stll a huge test, f enterprses can expand the scope of dstrbuton and offer free home delvery servce, ths huge cake wll gve e-commerce and logstcs enterprses a great reward. In ths paper, we can only use experence and knowledge from the perspectve of qualtatve analyss of the nfluence factors of the end of cty logstcs accordng to ISM technology. In order to deal wth the specfc ssues to be more accurate and practcal, we should also consder the dfferent contrbuton of each factor and make quanttatve analyss on the bass of qualtatve analyss to guarantee the accuracy of the analyss results. Acknowledgements Ths research work s supported by Natural Scence Foundaton of Chna: Reconstructed and analyzed nonlnear model for descrbng large-sze and complex genetc regulatory networks based on dynamc system ( ), Bejng Key Laboratory of ntellgent logstcs system (NO: BZ0211), Bejng Intellgent Logstcs System Collaboratve Innovaton Center, and 2013 feld major scentfc research projects of Bejng WUZI Unversty: Order pckng optmzaton problem research on removable shelves. References Ca, Y. (2014). Development paths of the end of the logstcs dstrbuton n Chna. Modern Logstcs, A5. Chen, P. (2013). Rsk Assessment and Preventve Measures of Fnal Dstrbuton. Logstcs Engneerng and Management, He, J., & Sh, X. (2013). End of the cty logstcs dstrbuton problem study. Logstcs Sc-Tech, Lan, B., & Wang, Y. (2011). Enterprse resource optmzaton and the enterprse value chan analyss. Journal of management scence n Chna, Le, N. (2014). The dffcultes and countermeasures of the end of E-commerce logstcs. Hebe Jaotong Vocatonal and Techncal College, Le, N., & Wang, Y. (2015). Dscusson on the end of the e-commerce logstcs. Busness, 239. L, Z. (2014). Study on End-Pont Collaboratve Logstcs Dstrbuton Based on B2C E-commerce Mode. Logstcs Technology, Lu, Y. (2016). Research on logstcs rsk evaluaton system of last mle of e-commerce supplers. Development Research, /j.cnk.kfyj Wang, Y. (1998). System engneerng theory, method and applcaton. Bejng: Hgher Educaton Press. Zhang, X. (2013, 3). Jont Dstrbuton Patterns and Decson-Makng Paths for. Research on Fnancal and Economc Issues,

9 Zhu, Z. (2012). Analyss of Routes of Urban-rural Integrated Termnal Logstcs Dstrbuton. Logstcs Technology, Copyrghts Copyrght for ths artcle s retaned by the author(s), wth frst publcaton rghts granted to the journal. Ths s an open-access artcle dstrbuted under the terms and condtons of the Creatve Commons Attrbuton lcense ( 171