Bridging Financial and Operational Gaps in Supply Chain Finance: An Information Processing Theory Perspective

Abstract

This paper explores the integration of financial and operational flows in Supply Chain Finance (SCF) through the lens of Information Processing Theory (IPT). Despite increasing adoption of SCF solutions like reverse factoring and trade credit, existing literature lacks a unified theoretical framework that captures both financial and organizational complexities. Drawing from 47 peer-reviewed articles in leading supply chain journals, this study identifies key SCF dimensions—task characteristics, environment, and interdependence—as primary sources of uncertainty and information processing needs. It then examines how IT systems, coordination mechanisms, and organizational design enhance processing capacity, enabling firms to build SCF capabilities such as risk assessment, supplier onboarding, and financial process standardization. These capabilities facilitate financial supply chain integration through data connectivity, embedded flows, and collaborative planning. The study contributes a comprehensive conceptual model that connects SCF uncertainties, processing strategies, and performance outcomes, addressing theoretical and managerial gaps. It further provides a foundation for future empirical research and strategic design of SCF systems to enhance supply chain resilience and financial efficiency.

1. Introduction

The growing complexity and ambiguity within international supply chains have furthered the requirement for combined financial mechanisms. However, our theoretical knowledge of how companies handle financial flows within networks of suppliers is disparate. These conditions have led organizations to look for alternative mechanisms like factoring, trade financing (Schäfer & Baumann, 2014), and inventory financing (Basu & Nair, 2012) to better manage working capital. As a reaction, Supply Chain Finance (SCF) has been a pivotal strategy for synchronizing financial flows with product and information flows with the goal of maximizing cash flow in the supply chain (Wuttke et al., 2013a, 2013b; Gelsomino et al., 2016).

SCF is engineered to minimize supplier risk, simplify processes, and harmonize information, financial, and material flows. It is especially useful in assisting financially constrained companies and strengthening the credibility of SC partners—suppliers, buyers, and financial service providers (Chen et al., 2022). Additionally, SCF solutions like reverse factoring (RF), trade credit, and third-party logistics (3PL) provider financing have extended access to financing for small and medium-sized enterprises (SMEs), resulting in lower borrowing costs and better cash conversion cycles (Pfohl & Gomm, 2009; Gomm, 2010; Hofmann, 2005).

Over the past decade, academic interest in SCF has expanded considerably. Researchers have addressed areas such as inventory decisions under trade credit, payment strategy interaction with replenishment decisions, and the role of financing services in the SC (Xu et al., 2018). However, despite this progress, comprehensive theoretical development remains limited. While a few review studies exist (X. Liu et al., 2015; Gelsomino et al., 2016; Xu et al., 2018), they are largely descriptive, often focusing on narrow aspects of SCF and lacking a unified theoretical foundation. In order to put the limitations of past reviews into context,

Table 1. Overview of existing SCF review studies. Source: Authors’ compilation based on X. Liu et al. (2015), Gelsomino et al. (2016), Xu et al. (2018), Tseng et al. (2021), and other SCF review literature.

Author(s) and Year	Focus of Review	Theoretical Foundation	Key Limitations
Cho et al. (2012)	Service supply chain performance measurement	Fuzzy-AHP framework	Financial aspects covered superficially; not SCF-specific
X. Liu et al. (2015)	Overview of SCF mechanisms and adoption	Non-explicit	Descriptive, lacks integrative framework
Gelsomino et al. (2016)	SCF solutions, adoption drivers, barriers	Transaction Cost Economics	Limited scope, does not integrate operational and financial flows
Xu et al. (2018)	SCF models in inventory/finance	Optimization models	Focused on operational modeling; fragmented without theoretical unification
Tseng et al. (2021)	Sustainable SCF through bibliometric analysis	Bibliometrics	Sustainability-specific, does not engage with broader SCF integration

outlines the key Supply Chain Finance (SCF) studies and their range. Although these reviews have progressed knowledge, they tend to be descriptive, piece-meal in focus, or confined to one viewpoint like sustainability or optimization, thus re-emphasizing the necessity of a theory-based synthesis like Information Processing Theory (IPT).

Even as SCF research has advanced, three essential gaps still exist.

First, current reviews of SCF are descriptive in nature and not integrated with a strong theory (e.g., Gelsomino et al., 2016; Xu et al., 2018).

Second, whereas research discusses financing mechanisms like buyback contracts (J. Shi et al., 2020) and portfolio financing (Dong et al., 2020), none of these link such mechanisms with operational aspects of SCF.

Third, while more recent studies highlight SME financing difficulties (Song et al., 2019; B. Liu et al., 2020) and SCF with a sustainability focus (Tseng et al., 2021), Information Processing Theory (IPT) has not yet been applied systematically to SCF.

To bridge these shortfalls, this research establishes an IPT-based framework that connects SCF uncertainties, processing mechanisms, and performance outcomes. Researchers like Templar et al. (2012) and Gelsomino et al. (2016) have identified the lack of a strong theoretical foundation as one of the main hurdles to the development of SCF research.

In response to this weakness, the current study utilizes Information Processing Theory (IPT) as a conceptual framework to study SCF. IPT considers companies to be information processing systems that deal with uncertainty through improving their capability to gather, process, and respond to information from their surroundings (Daft & Weick, 1984; Tushman & Nadler, 1978). This theme is especially suitable in the context of SCF, where operational and financial decisions are intricately connected and exposed to fluctuating external factors. Poor information processing may destabilize the coordination between financial flows and supply chain operations, particularly when there is uncertainty.

In SCF, IPT dimensions appear as follows:

• Task features: Operational–financial coordination within models such as buyback contracts (J. Shi et al., 2020) or financing a portfolio (Dong et al., 2020).
• Environmental uncertainty: Sectoral/regional financing disparities, for example, rural SCF inefficiencies in China (X. Liu et al., 2020).
• Interdependence: Collaborative financing mechanisms, e.g., power-configured trade credit (B. Liu et al., 2020) and risk-sharing among actors (Ying et al., 2020).

Therefore, IPT presents a robust basis on which to understand how SCF mechanisms increase information processing ability.

Although IPT has been widely used in fields of organizational strategy (Rogers et al., 1999; Trentin et al., 2012), global sourcing (Trautmann et al., 2009), production systems (Gong et al., 2014), and green supply chain management (Busse et al., 2017), its extension to SCF is still a largely untapped area. The current paper seeks to help address that gap by considering an IPT-based integrated framework of SCF. It systematically reviews literature to reveal how information processing needs—based on SCF task attributes, environment, and interdependence—can be aligned with processing abilities—facilitated by organizational structure, coordination mechanisms, and technology.

The long-term goal of SCF is to close the gap between operational and financial flows, thus maximizing end-to-end supply chain efficiency and resilience. Embracing the central function of information, this paper further emphasizes the necessity of managing order transactions, liabilities, and environmental data to mitigate uncertainty and investment risk (Gomm, 2010; Pfohl & Gomm, 2009). In addition, it synthesizes results from an extensive bibliometric and subject-matter review of SCF literature, building on the methodological building blocks established by Gelsomino et al. (2016) and Bals (2019), and providing in return an improved framework and research agenda.

Overall, this paper makes three significant contributions. First, it provides one of the most exhaustive theory-based reviews of SCF research to date. Second, it uses IPT to develop a consolidated conceptual model for SCF integration of financial and operating decisions. Third, it sets out particular research propositions and problem classes that can inform future research in this rapidly developing field.

Drawing on these gaps and the theoretical underpinning of Information Processing Theory (IPT), this research is informed by the following research questions:

RQ1: In what ways can IPT be used to conceptualize financial and operational flows’ integration in SCF?

RQ2: In what ways do SCF mechanisms—like buyback contracts, trade credit, SME financing, and portfolio financing—augment firms’ information processing ability?

RQ3: How can the IPT-based SCF framework inform empirical validation across different industries and regions, such as rural and agricultural areas?

Answering these questions allows this paper to place IPT as a synthesizing viewpoint for SCF research and to establish an organized agenda for future empirical analysis.

The rest of this paper is organized as follows: Section 2 introduces the supply chain finance relevant theories, and Section 3 introduces the research approach. Based on the literature reviewed and theoretical frameworks, Section 4 formulates an integrated conceptual model with associated propositions for supply chain finance. Lastly, Section 5 concludes the paper with a summary of its main implications and limitations.

2. Theories Used in Supply Chain Finance

Various theories have been employed in the current SCF literature, with resource dependence theory and agency theory being the most popular. These theoretical views typically belong to two broad families: financial theories and organizational theories. Research based on financial theory typically concentrates on factors like financing goals or collateral (e.g., pecking order theory) and funding sources (e.g., diversion theory). In contrast, organizational theory-based studies tend to investigate inter-organizational relationships (e.g., principal-agent theory, bargaining power theory, resource dependence theory, systems theory, and task interdependence), intra-organizational process (e.g., transaction cost theory and inventory theory), and adoption and implementation of SCF practices (e.g., innovation process theory).

Despite this diversity, a notable gap remains in the literature: no single theory has comprehensively addressed SCF from both financial and organizational standpoints. In addition, information management, which is central to effective SCF implementation, is frequently overlooked in theoretical discussions, thereby hindering a more integrated understanding of SCF systems.

To overcome this lacuna, this research recommends the usage of Information Processing Theory (IPT) as a theoretical lens for examining SCF. IPT describes the means through which organizations cope with uncertainty—stemming from task characteristics, environmental fluctuation, and task interdependence—by improving their ability to process information (Tushman & Nadler, 1978). In IPT, organizations vary in terms of their information processing requirements and establish different integration mechanisms to cope effectively with those requirements (Trautmann et al., 2009). The information processing model is presented in Figure 1.

Recent work has emphasized the multi-dimensional character of SCF and various mechanisms by which financial flows are aligned with operational flows. For the sake of conceptual distinction, we differentiate between embedded financial flows and cross-organizational financial cooperation. Embedded financial flows involve technology-led, automated coupling of financial transactions into operational processes (e.g., reverse factoring built into procurement systems in which payment is automatically triggered once invoices are authorized). Conversely, cross-organizational financing cooperation involves more extensive cooperative behaviors like joint financing agreements, credit guarantees, or mutual risk-management arrangements among buyers, suppliers, logistics service providers (LSPs), and financial institutions (de Goeij et al., 2020; Lin & Xiao, 2018).

Research on reverse factoring demonstrates the relevance of embedded flows in stabilizing working capital but concurrently underscores adoption issues based on dynamic market environments and uncertainty (Dello Iacono et al., 2015). On the part of SMEs, financial choices tend to be influenced by bounded rationality, opportunism, and trust, making it harder to implement otherwise financially appealing SCF deals (de Goeij et al., 2020). In addition, the analysis indicates not all companies can equally take advantage of SCF: Elliot et al. (2020) discovered that LSPs may possess resources to enable SCF but value capture is still challenging, implying cooperative integration past mere transactional integration is paramount.

Moreover, the literature on guarantee-based SCF models shows that structural mechanisms improve access to finance. For instance, supplier asset structures (Lin & He, 2019) and credit guarantees from core buyers (Lu et al., 2019; Lin & Xiao, 2018) can improve credit terms and lower risk exposure for banks. In addition, third-party or supplier partial credit guarantee programs have an important role in facilitating retailers’ access to capital in high-risk settings (Lu et al., 2019). To reinforce this, research on 3PL-based finance demonstrates how financial and operational service integration (for example, variable transport fee arrangements) can improve liquidity and supply chain efficiency (Huang et al., 2019). Blockchain adoption feasibility across industries demonstrates the digital foundations for SCF innovation (Erol et al., 2021).

Lastly, SCF models are increasingly being developed to take account of product quality risk (Jin et al., 2021) and multi-attribute decision variables such as service levels and bankruptcy costs (Yan & He, 2020). These papers emphasize the necessity to note that the effectiveness of SCF relies not only on the optimization of finance but also on relational, operational, and contextual characteristics. The IoT and blockchain technologies are increasingly being explored to mitigate information asymmetry in SCF transactions (L. Liu et al., 2021). This variation in methodologies reflects the need for an overarching theoretical framework like Information Processing Theory (IPT) that can explain uncertainties and complexities in decision-making across SCF mechanisms.

While IPT has found widespread usage in organizational strategy (Rogers et al., 1999; Trentin et al., 2012), global sourcing (Trautmann et al., 2009), inter-organizational information integration (Wong et al., 2015), production control (Gong et al., 2014), sustainable supply chain management (Busse et al., 2017), and supply chain risk management (Fan et al., 2017), it has been comparatively unexplored in SCF contexts. Nonetheless, IPT provides immense scope to enhance SCF research on two important grounds. Firstly, although earlier research on supply chain management has touched upon financial issues—such as maximizing cash flows (Brealey et al., 2007) and mechanisms of trade credit (Chauffour & Malouche, 2011)—it hardly ever looked at the information processing role. Second, while the importance of information in SCF has been recognized in earlier research (e.g., Pfohl & Gomm, 2009; Song et al., 2018), these contributions are largely descriptive and do not have a solid theoretical foundation.

Drawn by IPT, this research takes a two-lens perspective in examining SCF literature. The first dimension, requirements for information processing, is influenced by SCF task properties, environmental uncertainty, and interdependence among actors. The second dimension, information processing capabilities, includes organizational design, coordination and control systems, and information technology use. The analysis shows that SCF capabilities arise where there exists an appropriate fit between the information processing needs and the respective capabilities, providing a theoretically embedded account of SCF integration success.

3. Methodology

This study used 47 selected papers from the following journals: International Journal of Production Economics (25 papers), Journal of Purchasing and Supply Management (12 papers), International Journal of Physical Distribution and Logistics Management (5 papers), and International Journal of Production Research (5 papers).

As is clear from Figure 1, the review, in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, aimed at transparency and replicability. The process initiated with the retrieval of 450 records from databases such as Scopus, Web of Science, and ScienceDirect. During screening, 320 records were screened on titles and abstracts, and duplicates and non-relevant studies were excluded. The eligibility phase required full-text screening of 85 articles against inclusion criteria including SCF focus, relevance to financial–operational integration, and clear theoretical or methodological contribution. Ultimately, 42 studies were incorporated into the synthesis. This ensured that the resultant final dataset of studies was comprehensive and methodologically robust.

As supplementary to the systematic review, a bibliometric analysis was performed using SciMAT, which allows for the identification of research themes through the clustering of co-occurring words across chosen studies. As can be seen in Figure 2, four clusters are evident:

(i)

Financing Mechanisms—research on buyback contracts and portfolio financing that connects operating choices with fiscal measures (J. Shi et al., 2020; Dong et al., 2020).

(ii)

SME Credit and Knowledge Spillovers—studies emphasizing the impact on SMEs’ credit quality of inter-organizational networks and knowledge access (Song et al., 2019; B. Liu et al., 2020).

(iii)

Risk Management—articles that deal with data-oriented strategies to forecast and manage credit and financing risks (Fayyaz et al., 2021; Ying et al., 2020).

(iv)

Regional and Environmental Analysis—research comparing SCF from geographical and environmental considerations, such as rural inefficiencies and interregional differences (Tseng et al., 2021; X. Liu et al., 2020).

These clusters validate the fragmented state of SCF research and reiterate the importance of a uniting theoretical underpinning. They also form a structured foundation for building the IPT-based conceptual framework presented in Section 4.

To put the systematic review in perspective, we undertook a descriptive analysis of SCF research development in the last 15 years. The trend in SCF scholarship reveals a sharp shift from early themes to more intricate and interdisciplinary views.

Early phase (2005–2012): Initial SCF research largely focused on working capital management, trade credit, and factoring vehicles. Such papers usually discussed how buyers and sellers could utilize financing vehicles to enhance liquidity and minimize transaction costs, and where theories were limited (e.g., Hofmann, 2005; Pfohl & Gomm, 2009).

Middle phase (2013–2017): During this time, studies extended to cover integration of operational and financial flows. Researchers studied how financing tools—reverse factoring and inventory financing—could be integrated into supply chain decision-making. This phase also witnessed the emergence of empirical research into SME access to finance and how buyer–supplier partnership facilitated financial stability along the supply chain (Xu et al., 2018; Gelsomino et al., 2016).

Recent stage (2018–2022): In the last few years, from Figure 3 it is understood that SCF research has grown considerably in terms of depth and scope. Contemporary research focuses on risk management using high-level analytics (Fayyaz et al., 2021; Ying et al., 2020), financial–operational integration sustainability (Tseng et al., 2021), and regional themes like rural and emerging market SCF uptake (X. Liu et al., 2020). In addition, the integration of big data, digital platforms, and blockchain with SCF practices has opened up new levels of innovation and complexity (Bals, 2019).

This development emphasizes the fractured but growing nature of SCF research, affirming the necessity for a consolidating theoretical basis. In locating the bibliometric analysis and conceptual framework within this temporal context, the present study reinforces its place and explains how IPT can develop the field.

Besides the bibliometric mapping, thematic analysis was also undertaken to allow for interpretive exploration of the predominant research streams in SCF. Though bibliometric software like SciMAT points to structural interrelations between keywords, thematic analysis allows for richer conceptual knowledge of the literature. From the 48 studies that were selected, four overarching themes emerged:

• Financing Mechanisms. This body of literature examines how financing contracts and mechanisms can close operational and financial flows. For instance, buyback contracts treat capital-constrained newsvendor issues by coordinating finance and inventory (J. Shi et al., 2020), whereas portfolio financing introduces tax shield impacts in two-echelon supply chains (Dong et al., 2020).
• SME Constraints and Credit Access. A second consistent theme relates to the funding struggles of SMEs and the processes that can make them more credit-worthy. Spillovers of knowledge in supply chains enhance SME credit quality (Song et al., 2019), and power disparities between organizations influence trade credit in developing countries (B. Liu et al., 2020). Recent studies also highlight that SME credit quality is significantly affected by the strength of supply chain networks and information sharing structures (Ali et al., 2019). Regional differences are also essential, as demonstrated in Chinese rural SCF performance research (X. Liu et al., 2020).
• Risk Management. In the face of growing uncertainty in financial flows, some research emphasize predictive and preventive measures. Machine learning-based credit risk predictive models (Fayyaz et al., 2021) and text-mining tools to detect SCF risk determinants (Ying et al., 2020) are among the major contributions to this topic.
• Sustainability and Regional Differences. Another theme focuses on sustainability and regional considerations in SCF. Bibliometric studies illustrate high regional diversity in the adoption of SCF and reveal the importance of sustainable financing indicators in determining supply chain performance (Tseng et al., 2021).

Taken together, these themes show the complementary but fractured character of SCF research and emphasize the necessity for a common theory base, which this research delivers via the use of Information Processing Theory (IPT).

From each paper, the SCF Task Characteristics, SCF Task Environment, SCF Task Interdependence, Mechanisms for improving information processing capacity, SCF Capabilities, and Financial SC Integration are identified. In order to construct a conceptual framework for Supply Chain Finance (SCF) based on Information Processing Theory (IPT), this research conducted a qualitative content analysis of scientific articles published in top-ranked journals within supply chain management, logistics, and operations. The review aimed at the identification of theoretical constructs and empirical evidence concerning SCF and its correspondence with information processing requirements and capabilities.

Forty-seven peer-reviewed journal articles were chosen for a closer look. The choice was made on relevance to themes in SCF, richness in theory, and publication quality. These articles came from four highly respected journals within the field:

• International Journal of Production Economics (IJPE)—25 articles.
• Journal of Purchasing and Supply Management (JPSM)—12 articles.
• International Journal of Physical Distribution and Logistics Management (IJPDLM)—5 articles.
• International Journal of Production Research (IJPR)—5 articles.

These journals were selected due to high impact, reputation in the discipline, and listing in esteemed journal quality rankings (e.g., ABDC list).

All picked articles were screened for the purpose of drawing out important insights against six IPT-derived dimensions:

(1)

SCF Task Characteristics—the complexity and nature of tasks associated with SCF implementation and execution.

(2)

SCF Task Environment—external environmental aspects of uncertainty, regulation, or market volatility.

(3)

SCF Task Interdependence—the level of interdependence among SCF players (e.g., buyer, supplier, financier).

(4)

Mechanisms for Enhancing Information Processing Capacity—technological, structural, or process-related facilitators used to handle information flows.

(5)

SCF Capabilities—organizational competencies that enable effective SCF planning, decision-making, and implementation.

(6)

Financial Supply Chain (SC) Integration—the degree to which financial flows are coordinated and synchronized with physical and information flows within the supply chain.

A structured coding framework was employed to examine every article and determine relevant variables corresponding to the above classifications. Each variable was then classified based on whether it reflected an information processing need (stemming from task/environment complexity) or an information processing ability (organizational reactions to those needs).

This process of analysis facilitated the integration of theoretical findings and empirical trends across the studies and the development of a new conceptual model of SCF integration grounded in IPT. The model not only isolates the central variables influencing SCF performance, but also presents a diagnostic framework to determine the degree of fit of information processing demands and capabilities in different SCF settings.

Since this is a conceptual and theory-building research, we do not report “results” in the traditional empirical sense. Rather, the results are integrated into the bibliometric and thematic analyses (Section 3) and further synthesized into the IPT-based conceptual framework (Section 4). This aligns with the study’s goal of creating an integrated theoretical model instead of presenting statistical results.

4. Discussion

This section offers an integrated conceptual framework grounded in Information Processing Theory (IPT), connecting the various SCF elements—task characteristics, task environment, and task interdependence—with processes for enhancing information processing capacity, SCF capabilities, and financial supply chain integration. We assert that information processing needs, influenced by different sources of uncertainty, need to be aligned with suitable processing capacities. The extent of this “fit” governs SCF capabilities and integration outcomes.

4.1. Derivation of the IPT-SCF Framework

The IPT-informed SCF model is constructed through the synthesis of findings from the bibliometric and thematic analysis. More particularly, three IPT dimensions—task uncertainty, environmental uncertainty, and interdependence—were transposed to the four prevalent SCF research streams.

Task Uncertainty is tackled in the literature using contract mechanisms like buyback contracts and portfolio financing, where financial flows are synchronized with operational risks (J. Shi et al., 2020; Dong et al., 2020).

Environmental Uncertainty is found in sustainability-focused and local SCF research, which highlights the impact of outside context on funding behavior (Tseng et al., 2021; X. Liu et al., 2020).

Interdependence is even more pronounced in research on SME financing and credit availability, where inter-organizational relationships and power dynamics take center stage (Song et al., 2019; B. Liu et al., 2020). Interdependence is also pronounced in risk management studies, where analytical tools strengthen cooperative responses to uncertainty (Fayyaz et al., 2021; Ying et al., 2020).

By systematically relating these thematic findings to the IPT dimensions, the proposed framework (Figure 4) presents a theoretically informed, structured model for SCF financial and operational flow integration.

4.2. SCF Providers’ Uncertainties and Requirements for Information Processing

4.2.1. Characteristics of the Task

SCF task features inject uncertainty into financial decision-making through the complexity and uncertainty of bringing financial flows together with operations realities. Factors including complexity of bringing financial and operational information together (Moretto et al., 2019; Xu et al., 2018), liquidity pressure from disruption (Gelsomino et al., 2016), and asset specificity and risk valuation (Xu et al., 2018; Gelsomino et al., 2016) pose challenges that require more information processing.

Moreover, creditworthiness of the buyer becomes a central pillar for financing structures (Lekkakos & Serrano, 2016; Xu et al., 2018), and task uncertainty in supplier finance renders it more difficult for financiers to estimate default risk and repayment periods (Wuttke et al., 2013b).

Proposition 1a. 

Task characteristics-related uncertainties of SCF increase SCF providers’ information processing demands.

4.2.2. Task Environment

The SCF task environment adds another uncertainty from market-level as well as institutional sources. For example, heterogeneity among stakeholders (Moretto et al., 2019) makes financial coordination between firms more difficult, and financial exclusion of SMEs (Lekkakos & Serrano, 2016; Gelsomino et al., 2016) causes distorted access to financing.

Regulatory and institutional constraints (Song et al., 2018; Xu et al., 2018) also limit SCF adoption because of ambiguous legal frameworks, whereas market volatility and exogenous shocks (Xu et al., 2018) influence liquidity requirements and SCF demand. Lastly, underdeveloped financial infrastructure (Gelsomino et al., 2016; Xu et al., 2018) hinders real-time sharing of financial information.

Proposition 1b. 

SCF task environment-related uncertainties increase SCF providers’ information processing requirements.

4.2.3. Task Interdependence

SCF implementation relies on cross-functional and cross-organizational coordination; therefore, task interdependence is an important source of complexity. Strategic buyer–supplier relationships (Moretto et al., 2019; Lekkakos & Serrano, 2016), triadic relationships among buyers, suppliers, and financiers (Gelsomino et al., 2016; Xu et al., 2018), and mutual dependence for access to liquidity (Wuttke et al., 2013b; Lekkakos & Serrano, 2016) enhance coordination needs. Supplier capital constraints and competitive co-opetition dynamics also shape SCF adoption (Gu et al., 2021).

In addition, sharing information among partners (Moretto et al., 2019; Gelsomino et al., 2016) and payment/approval process coordination (Lekkakos & Serrano, 2016; Wuttke et al., 2013b) necessitate strong systems and integration so that SCF is not interrupted.

Proposition 1c. 

Interdependencies between SCF tasks add to the information processing needs of SCF providers.

4.3. Mechanisms for Enhancing Information Processing Capacity

In order to address the above uncertainties, SCF providers utilize a range of mechanisms to enhance their information processing capability. IT platform integration and real-time tracking of invoices and performance bring greater visibility to the SCF network (Gelsomino et al., 2016; Wuttke et al., 2013b). Digital supply chain platforms allow for quicker processing and coordination (Wuttke et al., 2013b; Xu et al., 2018). In addition, technology-facilitated risk assessments facilitate dynamic assessment of supplier risk and asset worth (Xu et al., 2018).

Sophisticated multi-criteria decision-making models support the analysis of financing approaches and choosing the best SCF tools (Guida et al., 2021).

Proposition 2. 

Increased IT integration, coordination systems, and organizational adaptability result in more SCF information processing capabilities.

4.4. Requirements–Processing Capacity Fit → SCF Capabilities

If information processing capacity is matched with task-oriented information needs, SCF providers generate greater capabilities. These consist of program management capability (Moretto et al., 2019), credit risk assessment based on operational data (Xu et al., 2018; Gelsomino et al., 2016), and resistance to interruption (Wuttke et al., 2013b).

Supplier onboarding (Moretto et al., 2019; Lekkakos & Serrano, 2016) and financial process standardization (Xu et al., 2018; Gelsomino et al., 2016) are also indicators of mature SCF programs that can adapt to different levels of supply chain complexity and volatility.

Proposition 3. 

Information requirements and capacity have a high fit, resulting in higher SCF capabilities.

4.5. SCF Capabilities Facilitating Financial Supply Chain Integration

4.5.1. Mapping Financial Network Structures

Strong SCF capabilities enhance buyer–bank–supplier data connectivity (Gelsomino et al., 2016; Lekkakos & Serrano, 2016) and assist in defining inter-organizational roles. These linkages enhance operational integration such that financial services can be provided exactly where and when they are required.

Proposition 4a. 

Mapping financial network structures advances operational integration within the financial SC.

4.5.2. Designing Financial Business Processes

Firms must harmonize financial processes in the core supply processes. Embedded financial flows in procurement (Xu et al., 2018; Gelsomino et al., 2016) and cross-organizational financial collaboration (Moretto et al., 2019) enhance SCF alignment. Application of centralized SCF platforms (Wuttke et al., 2013b; Xu et al., 2018) facilitates seamless financial transactions.

Proposition 4b. 

Designing financial business processes supports seamless process integration across SC partners.

4.5.3. Sharing Financial Information Systems

Shareability of financial information through technologies such as EDI or blockchain enables trust and efficiency. Co-planning between supply and financial functions (Moretto et al., 2019; Guida et al., 2021) allows for synchronized planning and realization, minimizing financing gaps.

Proposition 4c. 

Financial SC information integration is facilitated through sharing financial information systems.

The SCF component and important parameters and references are given in

Table 2. SCF components and parameters.

SCF Component	Important Parameter	Reference
SCF Task Characteristics	Complexity of integrating financial and operational data	Moretto et al. (2019); Xu et al. (2018)
	Buyer creditworthiness as basis for financing	Lekkakos and Serrano (2016); Xu et al. (2018)
	Liquidity pressure due to disruptions	Gelsomino et al. (2016)
	Asset specificity and risk valuation	Xu et al. (2018); Gelsomino et al. (2016)
	Task uncertainty in supplier finance	Wuttke et al. (2013a)
SCF Task Environment	Stakeholder heterogeneity	Moretto et al. (2019)
	Financial exclusion of SMEs	Lekkakos and Serrano (2016); Gelsomino et al. (2016)
	Regulatory/institutional limitations	Song et al. (2018); Xu et al. (2018)
	Market volatility and external shocks	Xu et al. (2018)
	Limited financial infrastructure	Gelsomino et al. (2016); Xu et al. (2018)
SCF Task Interdependence	Strategic buyer–supplier relationship	Moretto et al. (2019); Lekkakos and Serrano (2016)
	Triadic involvement (buyer–supplier–financier)	Gelsomino et al. (2016); Xu et al. (2018)
	Mutual dependency for liquidity access	Wuttke et al. (2013a); Lekkakos and Serrano (2016)
	Information sharing between partners	Moretto et al. (2019); Gelsomino et al. (2016)
	Coordination for payment and approval processes	Lekkakos and Serrano (2016); Wuttke et al. (2013a)
Mechanisms for Improving Information Processing Capacity	IT platform integration	Gelsomino et al. (2016); Xu et al. (2018)
	Use of digital supply chain platforms	Wuttke et al. (2013a); Xu et al. (2018)
	Multi-criteria decision-making frameworks	Guida et al. (2021)
	Real-time invoice and performance monitoring	Gelsomino et al. (2016); Wuttke et al. (2013a)
	Technology-enabled risk assessment	Xu et al. (2018)
SCF Capabilities	SCF program management capability	Moretto et al. (2019)
	Credit risk evaluation using operational data	Xu et al. (2018); Gelsomino et al. (2016)
	Resilience and adaptation of financial support	Wuttke et al. (2013a)
	Supplier onboarding and engagement capability	Lekkakos and Serrano (2016); Moretto et al. (2019)
	Financial process standardization	Gelsomino et al. (2016); Xu et al. (2018)
Financial SC Integration	Buyer–bank–supplier data connectivity	Lekkakos and Serrano (2016); Gelsomino et al. (2016)
	Cross-organizational financial collaboration	Moretto et al. (2019)
	Embedded financial flows in procurement processes	Xu et al. (2018); Gelsomino et al. (2016)
	Use of centralized SCF platforms	Wuttke et al. (2013a); Xu et al. (2018)
	Collaborative planning between financial and supply functions	Moretto et al. (2019); Guida et al. (2021)

.

The review of 47 sampled papers offers detailed insights into the information processing needs of SCF (task-driven characteristics, task environment, and task interdependence), information processing capacity enhancing mechanisms, and SCF capability development. These insights form the basis for building an integrated conceptual framework (Figure 2), which displays the prime propositions and relationships explicated in this section.

Figure 5 illustrates our conceptual framework linking SCF uncertainties, information processing requirements, and organizational mechanisms in the IPT perspective. Three types of uncertainty—task characteristics, task environment, and interdependence—generate differential information processing requirements. Capital limitation of suppliers, for instance, is a task-level uncertainty, and unstable interest rates or territorial credit conditions are an environmental uncertainty (Lin & He, 2019; Lu et al., 2019). Interdependence occurs where buyers, sellers, and financial institutions need to synchronize repayment dates and material flows (Yan & He, 2020).

To mitigate these uncertainties, companies employ means that increase information handling capacity. IT-supported embedded flows (e.g., automated reverse factoring platforms) decrease transactional uncertainty by giving immediate visibility to receivables (Dello Iacono et al., 2015). Cross-organizational collaboration, including credit guarantee schemes or joint financing contracts, decreases interdependence-related risk through redistributing capital access and monitoring tasks (Lin & Xiao, 2018; Huang et al., 2019). LSPs and 3PLs extend this further by bringing operational and financial flows together, thus acting as hybrid coordinators of material and capital (Elliot et al., 2020; Huang et al., 2019). Joint provision of logistics and finance by third-party logistics (3PL) providers has also been shown to influence SCF performance under conditions of demand volatility (Wang et al., 2019).

These mechanisms establish SCF competencies like supplier onboarding, standardized credit evaluation, and joint financial planning, which themselves drive increased levels of financial supply chain integration. P2P financing has also been found to stimulate firms’ R&D investment and innovation efficiency (Pan et al., 2021). The integration is realized by (i) embedded finance flows that are embedded and automatically connect payments to operational milestones, and (ii) cross-organization collaboration that promotes joint problem-solving and financial risk avoidance. By elucidating these interconnections, our framework illustrates the way IPT offers a holistic perspective to examine the operational and financial aspects of SCF.

4.6. Methodological Directions for Testing the Framework

Although the current research formulates a conceptual model, there are various methodologies available for use in future work to empirically test the model. Survey methods might assess SCF adoption perceptions, especially for SMEs and large buyers, and allow for quantitative analysis between uncertainty, information processing mechanisms, and SCF performance (de Goeij et al., 2020). Case study approaches would make possible greater understanding of industry- or region-based settings, for example, LSP-driven SCF models (Elliot et al., 2020) or retailer credit guarantees (Lin & Xiao, 2018). Simulation and system dynamics modeling, as used in reverse factoring uptake (Dello Iacono et al., 2015), offer another way to explore how embedded flows and collaborative mechanisms respond in different market dynamics. Such triangulation of approach would yield both generalizable data and context sensitivity to enhance theoretical development.

5. Conclusions

5.1. Theoretical Contributions

This paper provides a few significant theoretical contributions to the SCF literature. First, it rigorously reviews SCF literature using the Information Processing Theory (IPT) lens, thereby filling an important research gap. Whereas previous literature has been predominantly descriptive or dichotomized between finance- and supply chain-focused perspectives (Gelsomino et al., 2016), our research unites both streams of thought by framing SCF as a coordinated information processing problem. The model developed in this research brings together SCF task attributes, task environment, and task interdependence as main sources of information processing burden.

Second, we advance IPT as a solid theoretical framework for SCF scholarship. In contrast to earlier theories, such as resource dependence or agency theory, which are literally defined as narrow accounts of power dynamics or principal–agent relationships, respectively, IPT accounts for a whole understanding of how SCF actors process uncertainty through organizational structures, digital platforms, and decision-support systems (Tushman & Nadler, 1978; Daft & Weick, 1984). It shows that proper alignment between information processing requirements and capacities yields greater capabilities and integration in SCF.

Third, the article provides an integrated framework that interrelates SCF uncertainties, processing mechanisms, organizational capabilities, and supply chain–finance integration. This methodology integrates disjointed SCF research into an integrated theory-driven framework, emphasizing major propositions and interactions between various layers of the SCF architecture. This framework explains the facilitators for successful SCF integration, including integration of IT platforms, onboarding capabilities of suppliers, and operational–financial collaborative planning.

Lastly, this research determines important variables and constructs in 47 high-standard SCF articles and categorizes them using six IPT-guided categories. These contributions establish a solid foundation for the future of SCF research, especially on topics that include digital transformation, risk analytics, and multi-actor coordination in financial supply chains.

5.2. Practical Contributions

From a management perspective, this study highlights the need for embracing an information-oriented strategy for SCF design and implementation. SCF managers and decision-makers should realize that numerous causes of uncertainty—from buyer credit risk to regulatory complexity and interdependence of tasks—yield high information processing requirements. To satisfy these requirements, managers should invest in scalable IT platforms, build inter-organizational relationships, and standardize financial processes among supply chain partners.

Second, the design gives practical advice regarding matching the information processing needs with the capabilities for processing. Companies with low information capacity can subject themselves to major hazards—like delayed cash flows, financing constraints, or coordination breakdowns. By contrast, excessive investment in processing ability can create redundancy and raise costs. As a result, gradual, adaptive increases in information systems and governance frameworks are advisable.

Third, the research prescribes a list of SCF capabilities (e.g., risk assessment via operational data, supplier onboarding, financial support resilience) that can be developed by practitioners to drive financial supply chain integration. These capabilities act as a blueprint for companies that want to incorporate financing without compromise into procurement and logistics activities, thereby making working capital cycles more rapid and SC relationships more robust.

5.3. Limitations and Future Research

This research, although grounded in sound literature synthesis and theoretical reasoning, is limited to some extent. This is a conceptual study, and although it defines the information processing framework in crystal clear language, empirical validation is yet to be conducted. Future studies need to test the proposed propositions using case studies, surveys, or simulation models in various industries and geographies.

Second, while the framework identifies task attributes, context, and interdependence as sources of uncertainty, further disarticulation of uncertainty types (e.g., strategic versus operational; endogenous versus exogenous) can further contribute to SCF model design improvement.

Third, while this article highlights digital technologies (e.g., platforms, monitoring software) as enablers of process capacity, technology adoption versus organizational maturity dynamics in SCF environments is an issue that has not been explored comprehensively and requires more comprehensive exploration.

Fourth, the appropriateness of the described framework is culturally and geographically variable. For instance, Asian SMEs will prefer buyer guarantees due to their limited access to bank loans, whereas European SMEs will possess more developed institutional support but higher transactions costs (Lin & He, 2019; de Goeij et al., 2020). Sector-related factors also dictate SCF mechanism applicability. Manufacturing and consumer goods are more likely to gain from embedded financial flows, while industries with uncertain demand or poor credit history, such as agriculture or SMEs in developing markets, will find it difficult to implement SCF (Yan & He, 2020).

Fifth, while the architecture places importance on embedded and cooperation mechanisms, it does not have a direct interface with outside shocks such as supply shocks, regulator shocks, or product quality risks affecting financing performance (Jin et al., 2021). Future work should also consider crowdfunding-based SCF platforms in the context of re-globalization (Reza-Gharehbagh et al., 2021). Future research can augment the model to include such context drivers.

In developing the IPT-SCF framework, a number of promising directions for future work can be discerned:

Empirical Validation of IPT-SCF. Although the proposed framework integrates knowledge from existing work, empirical verification is needed. Case studies of banks, large buyers, and SMEs can identify how companies implement SCF practices to manage task and environmental uncertainties. Survey-based research can also verify the interdependence role in collaborative financing arrangements.

Cross-Regional Adoption and Institutional Contexts. SCF adoption is still very much subject to regional and institutional contexts. For example, differences in credit availability and financial regulation between Asian and European economies heavily influence the success of SCF adoption (Tseng et al., 2021; X. Liu et al., 2020). Cross-country comparative studies may further our knowledge on how cultural and regulatory variations affect SCF practices. Recent evidence shows that demand uncertainty strongly influences financing choices in constrained supply chains (Y. Shi et al., 2021).

Integration of SCF with Sustainability. SCF with sustainability focus is an emerging field. Embedding environmental and social performance into SCF structures has the potential to align financing with international sustainability agendas (Tseng et al., 2021). New frameworks can be explored where financing is aligned with sustainable sourcing, circular economy principles, and carbon-reduction actions.

Digitalization and Fintech Applications. Increased use of big data analytics, artificial intelligence, and blockchain-based financing platforms can influence SCF practices. Fayyaz et al. (2021) and Ying et al. (2020) mention the potential of digital tools in anticipating and handling financing risks. Research in the future should analyze how fintech innovations improve information processing abilities in SCF and reduce risk in intricate global supply chains. The integration of digital finance into SCF has been linked to enhanced supply chain resilience (Zhang et al., 2022).

Together, these directions emphasize the need to bridge theoretical work with practical wisdom so that SCF research stays attuned to its relevance in managing financial as well as operational issues in fast-changing global environments.

In general, this paper is one of the first to extend Information Processing Theory comprehensively to SCF and propose a theoretically grounded model that captures the multiaspect nature of coordination of operations and finance. It has significant theoretical and practical implications and lays a strong foundation for future empirical research into SCF integration and capability development.