Keywords

1 Introduction

Logistics resource sharing employing collaboration strategy is increasingly becoming imperative nowadays. Through collaboration, companies reduce costs, improve quality of service, gain market position, minimize investment, as well as reducing emissions and congestion (Xu 2013). In Less-Than-Truckload (LTL), collaboration provides opportunities to exploit synergies in excess capacity, decrease lead times, and increase asset utilization (Peeta and Hernandez 2011). Despite of realized advantages, practical resource sharing under logistics collaboration is difficult due to many barriers, including the lack of trust (Xu 2013). Trust appears a primary obstacle limiting transport collaboration (Graham 2011; Hu et al. 2011) and its lack jeopardizes collaborative efforts (Hu et al. 2011). This lack of trust results into companies hesitating to share logistics resources like vehicle capacities due to uncertain outcomes of the perceived collaboration. While attempts to address trust problem in creation phase exist, there are limitations to investigation of trust in the operational phase of the collaborative organizations.

Further to performance-based trust employed in creation phase, trust in operational phase involves actions and interactions of the partners. For this reason, trust-building approaches employing only partner’s “performance” (Seifert 2007; Asawasakulsorn 2009) is appropriate for partner selection and insufficient to daily execution of collaboration. Instead, such approaches must integrate partners’ trusting actions and interactions occurring in operational phase. A pre-condition to this trust-building strategy comprises a feasible representation of trustworthy interactions among partnering entities. This representation is achieved by establishing a fundamental framework of trust-based interactions.

Such trust framework supposes to analyze as well as describe collaborative interactions of the partnering entities. Pursuant to the required trust framework, Collaborative Transportation Management (CTM) (VICS Logistics Committee 2004) and the conceptual framework of behavioral multi-agent model (Okdinawati et al. 2014) have provided some insights. They altogether identify CTM partners (agents), characteristics, interactions, and information exchange as well as required operating environment. Similarly, beyond identifying forms of collaboration within logistics network, Peeta and Hernandez (2011) have identified shippers and carriers as potential partners for exploiting LTL synergies. However, these works are unintended to represent trust relationships in collaborative supply networks. They lack an aspect of trust-based interactions purported to building trust supporting logistics and transportation collaboration. Moreover, Laeequddin et al. (2012) present an integrated conceptual model for trust building. The model addresses trust building from risk perspective in dyadic relationships. However, it does not support collaborations exceeding dyadic relationships and it lacks approaches to measure and assess trust. Thus, extending and integrating the model beyond its current purpose is highly needful.

The objective of this research therefore is to establish a trust framework. The framework is established by considering agents’ collaborative interactions contextualized to sharing of vehicle capacities in logistics and transportation. In particular, the research identifies and specifies key partnering entities, their trustworthy characteristics, roles, tasks, exchanged information as well as perceptions. The trust framework is imperative to designing of trust models aimed to empirically investigate trust among collaborating entities.

2 Trust in Collaborative Networked Organizations

Emerged cloud computing platforms have lifted up the concept of collaboration with new push. It has enabled configuration of easy and feasible supply networks globally. In logistics and transportation, cloud computing platforms facilitate management of underlying collaborative processes to enable efficient flows of materials and information. There are improvements in demand forecasts and capacity planning. However, besides introducing new business models, cloud enabled collaborations pose challenges to building trust in new arisen partner relationships. Thus, this section reviews trust requirements under the settings of cloud-enabled collaboration, followed by prospective integration of underlying models.

2.1 Building Trust in Cloud-Enabled Collaborative Environments

Cloud computing platforms have brought in new collaborative environments. They have limited physical interactions by introducing networked society in which online trust outweighs offline trust. As online trust lacks face-to-face interactions, cloud-enabled collaboration needs appropriate trust mechanisms. To overcome this deficiency, most of the online trading partners apply “reputation systems and social graphs” (Jøsang et al. 2007; Kwan and Ramachandran 2009) to build trust in peer-to-peer business relationships. These reputations systems, however, can suffer unfair ratings by buyers and sellers, but additionally, discriminatory behaviors of the seller (Dellarocas 2003). On top of these mechanisms, investigating partners’ trustworthy behaviors comprising of actions and interactions within cloud-enabled collaboration is crucial. A prerequisite to this investigation is a contextual specification of trust inherent in partners.

While trust is a context-specific construct, it challenges studying trust in all contexts (Nielsen 2011). With this view, trust contexts this paper applies are specified, considering: trust definition, trust embeddedness, and trust-building approach, as well as level of trust analysis. First, as this paper addresses trust problem in inter-firm collaboration, a trust definition in Mayer et al. (1995) is adapted. That, trust is a level of confidence trustor-party develops into trustee-party based on the expectation that trustee-party will perform a particular action necessary to trustor-party, irrespective of the ability to monitor or control trustee-party. This definition aligns to a notion of trust-as-choice or decision because it involves trusting behaviors in trust-related exchanges (Li 2012). A second context refers to trust embeddedness within actors. Laeequddin et al. (2012) highlight that trust is embedded within both actors, trustee and trustor. Trust embedded within trustee relates to trustee’s competence, while the latter is conceptualized as feelings and emotions (Laeequddin et al. 2012). In this paper, trust as embedded within trustee is specified, because such trust is rational, measurable and least of psychology. Third, while the literature proposes building trust from perspectives of “performance” (Seifert 2007; Asawasakulsorn 2009) and risk (Laeequddin et al. 2012) the latter perspective matters the most. The preference grounds in reliability-based trust, a co-approach to trust building in the perspective of risk-worthy relationships. Fourth, the literature (Delbufalo 2012; Nguyen and Liem 2013) identify three levels to trust analysis: inter-personal, inter-group, and inter-organizational. Subject to trust inherent to inter-firm collaboration, this paper analyzes trust at inter-organizational level. Considering these arguments together, trust is contextualized as embedded within trustee, under risk-worthy perspective, and analyzed at inter-organizational level.

2.2 Collaborative Logistics and Transportation

Literature refers to Collaborative Transportation Management (CTM) as a holistic process that brings together supply chain trading partners and service providers to drive inefficiencies out of the transport planning and execution process (VICS Logistics Committee 2004). It desires fulfilling inability of Collaborative Planning, Forecasting, and Replenishment (CFPR) in executing order processes (VICS Logistics Committee 2004). In place of CFPR, CTM improves performance by reducing dwell time, dead miles, and optimizing transport asset utilization.

There are similarities among “development phases of collaborative enterprise” (Thoben and Jagdev 2001), “integrated CTM business process” (VICS Logistics Committee 2004), and “planning and management decisions within transport logistics” (Gonzalez-Feliu and Morana 2011). While collaborative enterprises develop in a life-cycle of four phases: preparation, creation, operation, and decomposition; the remaining develop in three phases. Illustratively, members prepare to collaborate by selecting trustworthy partners (creation) to start sharing resources (operation), and their alliance dissolves at the end. Within CTM business process of the transport logistics, decision-making and management by partners occur at three levels: strategic, tactical, and operational. To comprehensively understand partners’ trustworthy behaviors; preparation, creation, and operation phases are proposedly merged with strategic, tactical, and operational phases respectively. To that effect, this paper establishes and formalizes three phases/stages appropriate to model agents’ trustworthy actions and interactions. They are: (1) selection and front-end agreement occurring in strategic level; (2) planning/order forecast occurring in tactical level, and (3) operational stage whereby actual delivery are executed.

Nevertheless, literature describes three categories of partnering entities, which this paper refers to as “partners”, “actors,” or “agents.” VICS Logistics Committee (2004) and Okdinawati et al. (2014) have identified shippers, carriers, and receivers as CTM potential partners. Gonzalez-Feliu and Morana (2011) have identified loaders (sender and receiver), logistics providers, and transporters as typical actors. Although other stakeholders like representatives of governing units exist, pursuant to trust building, shipper, carrier, and receiver are relevant partners.

3 Research Methodology

A trust framework depicting agents’ interactions to logistics and transport collaboration is conceived on a foundation of theoretical body of knowledge in the literature. The conception engages knowledge of collaborative networks, logistics and transportation, agent behavior as well as trust (Fig. 5.1). Collaborative network contributes base concepts functional to identify life-cycle and essential components constituting collaborative enterprises. Being an application domain, logistics and transportation are necessary to defining business requirements processes. Similarly, trust concepts in supply chain and logistics as well as agents’ behavior concentrating on transport collaboration are utilized to capture domain-specific connotations.

Fig. 5.1
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Methodology applied to conceive the trust framework

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Development of the framework proceeds by integrating strengths of the existing frameworks and models to fill limitations previously outlined. This integration is constituted by: (1) CTM model and its business processes (VICS Logistics Committee 2004); (2) behavioral multiagent model for collaborative transportation (Okdinawati et al. 2014); (3) an integrated conceptual model for trust building in supply chain partners relationship (Laeequddin et al. 2012), and (4) enterprise development phases (Thoben and Jagdev 2001) (Fig. 5.1). These models constitute prominent literature whose critical analysis prior to selection is unpresented because of space limitation. Thereafter integration, resulting composition is extended to provide trust-building requirements comprising of features, actions, and interactions of agents. Moreover, regarding vehicle sharing, the trust framework establishes crucial trust relationships among partnering agents like shippers, carriers and receivers.

4 Conception of the Trust Framework

To conceive trust framework, the term “agent” in place of “partner” is formalized to co-establish a linkage with prospective agent trust models whose development will apply this framework. This conception falls in three stages (Fig. 5.2). Three agents: shipper, receiver, and carrier are formalized as key partnering entities, with roles of producing, ordering/receiving, and moving of goods respectively. Nevertheless, depending on collaboration and trust building requirements, each agent can consists of more than one actor servicing similar role. These agents possess distinct perspectives with respect to production, distribution and demand of goods. This paper refers to this perspective as perception. Perception represents agent position to synchronized decision-making in relation to underlying issues require deliberation.

Fig. 5.2
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Conceptual trust framework depicting agents’ interactions in logistics collaboration

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Diverse interpretations, understandings, and implementations by partnering agents on production, distribution, and demand of goods create difficulties and mistrusts. The mistrusts arise whenever a satisfactory compromise is unreached among shippers, receivers, and carriers. Although there are many perceptions creating mistrusts, seven perceptions in (Okdinawati et al. 2014) are adapted and customized to needs of trust building. These perceptions (Fig. 5.2) are distinctly inherent in shippers, receivers, and carriers. Illustratively, shippers perceive producing goods based on capabilities and capacity (P1), as well as fixing production quantities (P5). Receivers have perceptions on uncertain market demand (P2), and unguaranteed on-time delivery (P8). Similarly, carriers perceive: increasing profit by increasing transportation rates (P3); offering limited carriage capacity (P4); fixing delivery quantities (P6); and on their full carriage capacity (P7). These perceptions are further described in subsequent paragraphs and subsections.

These perceptional differences create conflicts or “dilemmas” (Bryant 2004; Bennett 2004; Okdinawati et al. 2014) and consequently multiplying mistrusts. Aiming to model trust building, this paper emphasizes on “two dilemmas belong to collaboration: co-operation and trust dilemma” (Bryant 2004; Okdinawati et al. 2014). Bennett (2004) defines these dilemmas as follows: X has a cooperation dilemma if he has an improvement from his position, and; X has trust dilemma if Y can improve by moving away from X’s position. By thoroughly analyzing these dilemmas as well as extending them to requirements of trust building, arguably, they describe similar context. This context roots from the concept of trust embeddedness. The dilemmas depict a mistrust situation whereby trustor-agent doubts whether trustee-agent will comply with established agreements.

To resolve perceptional conflicts, one has to synchronize decisions toward deliberate compromise. For example, in P5: shipper and receiver have a conflict because receiver make orders based on market demand. Therefore, a compromise is required to negotiate, whereby one agent convinces other agents to own perceptional position or follow them otherwise. The ability to negotiate stems from agent’s internal ability, to either release or hold its perceptional position. Subject to which perception prevails or is compromised to, it commonly result into variant trust effect. The variance in trust effect depends on the extent of realized fairness with comparison to prior developed expectation.

4.1 Selection and Front-End Agreement

In creation stage (Fig. 5.2) agents establish strategic agreements thereby developing an intention to trust. According to Laeequddin et al. (2012), the intention to trust employing characteristics trust building is referred to as a propensity to trust. It is an initial willingness of partnering agents to collaborate. To develop propensity to trust, trustor-agent determines trustee’s characteristics as to whether they satisfy the extent of its intention. These characteristics are unlimited to scope of geographical location, previous trustworthy relationships, production and carriage capacities, as well as market demand (Fig. 5.2). Initially, development of the propensity to trust involve three tasks: invitation, submission, and assessment. The agent taking initiative to collaborate, called broker, invites prospective agents to a collaborative opportunity. Interested agents apply by submitting required information. Information describing previous trust relationships is directly accessed by broker from the community in which the agent resides and operates. On submission, broker assesses capabilities of the agents as to whether they satisfy specificity of the prospective consortium, and publicize results. On receipt of results, applicant agents can: accept the proposal, suggest adjustments, or reject it. If the proposal is rejected or suggested to adjustments, broker adjusts strategic structures (capabilities) until acceptable or terminates it. Besides characteristics trust building, the propensity to trust develops as well from the compromise reached by agents.

Alongside previous highlights, prior to passing strategic agreement, four perceptions must be deliberated. These perceptions are briefly presented together with the position of each agent. First, in P1: as shipper perceives producing based on its capabilities, receiver perceives the shipper to produce based on demand, while carrier remains in neutral position. Second, in P2: whereby receiver positions itself to uncertain market demand, both shipper and carrier perceive certainty in market demand. Third, in P3: as carrier perceives increasing profit by increasing transport rates, both shipper and receiver perceive him to increase profit by reducing transportation cost. Fourth, in P4: while carrier perceives limited carriage capacity, both shipper and receiver are in a position that carrier should offer unlimited carriage capacity. A detailed representation of the deliberate compromise on agents’ position will constitute a corresponding trust model, which is not part of this work.

4.2 Engagement and Order Forecast

Agents engage in collaborative actions thereby forecasting orders and developing rational trust (Fig. 5.2). Rational trusting is a deliberate action to trust, expressed as the degree of trust the trustor-agent develops in trustee. It is established depending on existing facts. To develop rational trust, agents execute many tasks. Specific tasks include order extension, load building, agreement on sharing scheme, and establishing expectation. Hereby a belief is, collaborating agents have more accurate information about demand and production quantities. Additionally, relying on shipment forecasts, carrier begins to build load and assigns to available trucks to early determine carriage needs. Furthermore, considering proportional scheme and Shapley values incentive schemes, agents urge deliberating which scheme they apply. On successful executions of these tasks, agents negotiate to compromise on arising perception. This stage comprises of three perceptions. They are briefly described to illustrate how specific agent perceives, and what are positions of the rival agents. First, in P5: as shipper perceives producing fixed quantities, receiver perceives the shipper to produce consistent with demand, while carrier is unaffected by the perception. Second, in P6: the carrier perceives to deliver fixed quantities, while shipper and receiver perceive that receiver should fluctuate the delivery consistent with demand. Third, in P7: carrier perceives a delivery to full capacity of its carriage, while receiver and shipper are reluctant to whether vehicle is full or not. Again, a resolution to these conflicts is a synchronized decision applying negotiating power to persuade other agents to own perception or follow them otherwise.

4.3 Physical Distribution

This is an execution stage, whereby goods are moved to indeed realize collaborative expectations, also termed as “actual score”. Actual scores realized constitute a crucial feedback, signaling the trustor-agent about the confidence, trust, it developed into trustee. This feedback is either below, within or above the expectation developed in prior. To realize this score, several tasks are executed. Firstly, carrier agent leverages shipment forecast depending on offered orders, and it checks for carriage constraints (if any) and leverage them accordingly. It secondly configures actual order and prepare it ready for distribution. Thirdly, carrier picks up and delivers inventories to their point of utility. Finally, the broker activates accounting process to reward partner agents. Hereafter, each agent is provided with records about operating performance resulting from executed collaboration that it compares with its prior expectations. Moreover, agents have further perceptions relating to collaboration performance. They include visibility information, lead time, responsiveness and on-time delivery. Fortunately, to these perceptions, all agents have same position except for on-time delivery (P8) for which carrier perceives a delay possibility.

5 Conclusions, Implications and Outlook

Trust building is long-term multi-disciplinary agenda in collaborative networked organizations including those in supply chain and logistics. It is however that majority of literature address trust in view of history, context, process, role, measurement as well as evaluation. Beyond these views, it is known that mistrusts root also from collaborative actions and interactions of the partnering agents. While comprehending on this view, empirical studies to investigate agents’ trustworthy interactions and respective behaviors in real world of collaborative scenarios are scarce. This paper fulfills this literature gap by initially establishing the conceptual trust framework. The framework depicts trust-based interactions of the partnering agents to address the question of trust building amongst entities sharing logistics resources. It depicts key partnering agents together with their trust-based roles, characteristics, tasks, perceptions as well as information exchange. Additionally, propositions on how agents develop the propensity to trust, rational trust, as well as benchmarking expectation against the reality are established. Moreover, agents’ trustworthy interactions this framework represents, inspire a significant trust building approach, which employs analysis of character behaviors and operating performance.

The proposed framework is substantially imperative in guiding the design of trust models purported to empirical investigation of trust amongst agents sharing logistics resources. To the large extent, this framework represents collaborative interactions aimed to elicit trust-building approaches in operational phase. It provides a clear understanding on mistrusts situation as well as trust scenarios agents undertake. A basis to validity of the proposed trust framework is largely determined by employed methodology. The framework is developed by integrating and extending prominent frameworks and models. Future research works are unlimited to design and evaluation of trust model resulting from this framework.