财务报表分析外文文献翻译2014年译文3140字

文献出处：Hofmann E, Lampe K. Financial statement analysis of logistics service providers: ways of enhancing performance[J]. International Journal of Physical Distribution & Logistics Management, 2014, 43(4): 321-342.

（声明：本译文归百度文库所有，完整译文请到百度文库。）

原文

Financial statement analysis of logistics service providers: ways of

Enhancing performance Hofmann and Lampe

Hofmann; Lampe

1 Introduction

In recent years, the demand for global logistics services has been increasing consistently ([28] Harrison and van Hoek, 2010). In order to compete in global markets, companies in all industry sectors strive for improved efficiency, so that logistical performance has become a substantial business challenge and key success factor ([8] Bowersox et al. , 2007; [9] Branch, 2009; [37] Liu and Lyons, 2010). To meet this challenge, companies whose core-competencies do not include logistics activities tend to outsource these functions to logistics service providers (LSPs) ([34] Lieb and Bentz, 2005a). Due to this development and to fulfill customer requirements, LSPs have broadened their scope of services, also in order to meet intensified competition.

Besides the range of services, the financial performance of LSPs is an important criterion for outsourcing decisions ([23] Gotzamani et al. , 2010). However, the trend towards outsourcing is not the sole reason for the growth of the LSP market. Globalization, the increased importance of knowledge-based consulting services, as well as the trend towards

It is remarkable that, despite the relevance of financial information relating to LSPs, researchers have so far paid little attention to the financial analysis of LSPs. As [37] Liu and Lyons (2010, p. 547) stated, practitioners would benefit from understanding the correlation between the performance of

LSPs and the various types of service provision,

By means of balance sheet analysis, this paper poses to answer the following research questions: RQ1. Is there a

RQ2. Are the asset-, capital- and liquidity-structures of LSPs dependent on their specific characteristics?

RQ3. Which financial indicators positively influence profitability of LSPs?

RQ1 can be considered as the main question raised in this paper, and RQ2 and RQ3 the sub-questions. For the purposes of analysis, LSPs are clustered into six groups, depending on the scope and nature of services offered. With this segmentation, we rely on the work of [37] Liu and Lyons (2010), who analyze the relationship between service provision and financial performance.

2 Background, methodology and sample selection

In Section 2.1, the methodology of financial statement analysis and integration of contingency theory are described. A detailed overview of sample selection is given in Section 2.2 and the Appendix.

2.1 Financial statement analysis and contingency framework

The financial statement analysis investigates the current and future financial, capital and income situation of companies. Amongst other sources, the analysis is based on information from the annual balance sheet and considers historical and present data and information ([20] Fridson, 1991). The financial statement analysis enables the depiction and interpretation of financial situations and developments ([6] Bernstein, 1990). It is one of the most common business analysis methods and the basis for further analysis in this paper.

The first step in the financial statement analysis presented in this paper is the collection of relevant

information about the LSPs to be analyzed. Firm-specific and financial information from Bloomberg and Factiva web database, which is based on FactSet data, were used. Bloomberg as well as FactSet are providers of company information and financial data. Furthermore, information publicized by the analyzed companies (especially the annual balance sheets) serves as an additional data source.

The focus of financial statement analysis is the determination and evaluation of KPIs, which enables a detailed overview of a company. KPIs illustrate the strengths, weaknesses and aberrations which form the basis for comparisons and valuations ([48] Penman, 2001). For the financial statement analysis in this paper, asset, capital, liquidity and profitability KPIs have been chosen, referring to [24] Granhof et al. (1993) and [22] Gibson (1982).

2.2 Sample selection and cluster characterization

Cluster formation, LSP selection (peer group) and the allocation of LSPs to cluster groups were conducted as follows.

The first step was the definition of LSP clusters. LSPs are any companies which perform logistics activities on behalf of others ([16] Delfmann et al. , 2012). Due to the broadness of the term LSP, six clusters are formed with regard to scope of services offered by the LSPs and related aspects (e.g. duration of business relationship, degree of integration (Figure 2 [Figure omitted. See Article Image.]). The clusters are: sea freight, railway, trucking, courier-, express-, parcel- service (CEP) LSPs, third-party (3PL) LSPs and fourth-party (4PL) LSPs.

The selected LSP clusters depend on:

- The scope of services provided ([68] Zacharia et al. , 2011; [61] Stefansson, 2006), from basic services like transportation and warehousing (scope of service: low) to value-added services ([5] Berglund et al. , 1999) as well as supply chain coordination ([64] van Hoek and Chong, 2001) (scope of service: broad).

- The degree of customization, from low, meaning standardized products, to high, meaning customer specific solutions ([61] Stefansson, 2006; [5] Berglund et al. , 1999).

- The degree of integration and duration of business relationship ([57] Skjoett-Larsen, 2000; [2] Bagchi and Virum, 1998; [43] Murphy and Poist, 1998), referring to the strategic dimension of LSPs. Companies in the clusters sea freight, railway and trucking are carriers, meaning transport operators that haul products ([54] Sheffi, 1990; [56] Sink et al. , 1996). These services are also referred to as basic services, like transportation or warehousing.

3 Balance sheet analysis of LSP clusters

In the following four sections, selected KPIs are discussed. For reasons of relevance and to enhance the clarity, only the six LSP clusters are discussed (not Top and Flop or the Big and Small 20 clusters

that are also listed in Table III).

3.1 Asset structure of LSPs

The industry sector of LSPs is characterized by an asset structure ([1] Africk and Calkins, 1994; [41] Muller, 1993; [68] Zacharia et al. , 2011). In the past, LSPs had their own exclusive transportation fleet and warehouses ([54] Sheffi, 1990). Orders were executed by means of the company's own capacities, so that LSPs recorded large transportation and warehousing assets in their balance sheets.

[1] Africk and Calkins (1994) had already questioned whether asset ownership still had any real meaning for logistics services, their quality, costs and risk. In recent years, the development of LSPs operating without the use of their own assets could be observed. Globalization, the pursuit of excellence and efficiency constraints led LSPs to adapt their business model to the market and customer demands. The logistics industry has experienced several phases of diversification over the past decades, which also led to a diversified asset structure context in logistics ([11] Cheng and Tsai, 2009).

Our analysis of selected LSP clusters reveals a clear difference between asset structures. The comparison clearly indicates which operators fulfill the role of coordination and which provide asset-based services. The most noticeable difference is clearly identifiable between the clusters of carriers and 4PL LSPs. While the asset structure of carriers consists of a high proportion of non-current assets, the asset structure of 4PL LSPs demonstrates the converse. Due to the service scope of 3PL and CEP LSPs, that is, between carriers and 4PL LSPs, their asset structure is also located between these two poles. Unlike 4PL LSPs, CEP LSPs and 3PL LSPs offer physical transportation on their own and, compared to carriers, they outsource services and work in partnerships with other LSPs. To sum up, the asset structure of LSPs indicates the extent to which LSPs accomplish, for example physical transportation services themselves or subcontract to other LSPs. The higher the degree of customization and integration as well as scope of services and average duration of business relationships (Figure 2 [Figure omitted. See Article Image.]), the lower the intensity of investment, meaning the non-current assets to total assets ratio, and the asset intensity 1 (non-current assets to current assets ratio) (Table III [Figure omitted. See Article Image.]). The asset turnover rate increases with increasing asset intensity 2 (current assets to non-current assets ratio). This indicates that non-current assets generate less turnover than current assets. The intensity of investment is also an indicator of asset flexibility (the lower the intensity of investment, the greater the asset flexibility): carriers have, due to their need for transportation assets, limited flexibility in comparison with the non-asset-based clusters.

3.2 Capital structure of LSPs

The capital structure reveals how assets are financed, by debt or equity ([39] Modigliani and Miller, 1958). The debt-to-equity ratio is the major indicator for financial risk assessment ([7] Bhandari, 1988).

As debtors have to guarantee payback, debt capital is relatively cheap compared to equity, but associated with higher risk, because illiquidity may lead to foreclosure. Higher costs of equity can be ascribed to payments to stockholders in the form of dividends ([59] Speh and Novack, 1995).

译文

物流服务公司财务报表的分析:提高业绩的方式

霍夫曼；兰普

1 引言

近年来，全球的物流服务需求不断地增加(哈里森和赫克，2010)。为了应对全球市场竞争，所有物流行业的公司都在争取提高业绩，以便物流服务绩效能成为一个实质性的业务挑战和关键成功因素(鲍尔索克斯等，2007，布兰奇，2009，刘和里昂，2010)。为了迎接这一挑战，那些核心竞争力不包括物流活动的企业都倾向于把这些功能外包给社会上专业的物流服务提供商(比如：第三方物流公司)(里布和本茨 2005)。由于这种发展趋势和以及为了更好地满足客户需求，物流服务商逐步扩大了服务范围，以满足竞争的加剧。

除了物流服务范围，物流服务商的财务业绩是外包决策的一个重要准则。然而，外包的趋势不是物流服务市场增长的唯一原因。全球化、基于知识的咨询服务的重要性的增加，以及一站式服务趋势，这些都是外部影响因素，“规模经济”和“范围经济”是物流服务公司增长的内部驱动因素(佩尔森和维姆，2001)。

物流服务商已从简单的运营商发展成综合性的物流服务提供者。为了保持经济增长，可以采取各种战略措施，包括组织成长，并购或与其他物流服务商建立合作。在任何情况下，财务结构或关键绩效指标(kpi)都为公司提供了重要的信息，就组织成长和资本而言，都适用于企业的信用评估，也可以提供关于并购收购目标的一般性信息(哈基宁等，2004)，以及评估有关的合作伙伴潜在的财务状况。

值得注意的是，尽管财务信息的相关性与物流服务公司有关，但是目前研究人员很少关注物流服务商的财务分析。里昂(2010)说，如果物流从业者理解物流服务商的业绩和各种类型服务之间的关系，那他们将从中受益，“制定适当的策略充分利用其商业潜力和减少投资风险”。资产负债表分析和关键绩效指标的建立，都为分析公司的财务状况和公司的业绩提供了方法。很少有研究对物流服务商的财务业绩进行分析。埃林等2003年遵循客观的方法(如：使用财务数据的绝对值)，分析交通运输行业的网络利用率和财务业绩之间的财务评估。帕拉蒂斯在2007年

评估了每一个财务指标。最后，刘和里昂于2010年专注于毛利率和销售增长的研究。相反，埃林等人则遵循一个主观的方法，来评估财务数据(如：调查或访谈)。到目前为止，专注于物流服务商资产负债表的分析研究是非常有限的。因此，对于物流服务公司的财务结构和业绩的分析是很迫切的。

通过资产负债表的分析,本文回答了以下研究问题:

为物流服务公司有“独特的”资产负债表结构吗?

物流公司的资产和流动资本依赖于他们的特定特征吗?

这些财务指标对物流服务商的盈利能力产生积极影响吗?

问题1可以被认为是本文提出的主要问题，问题2、3则是延伸性的问题，分析的目的，物流服务商基于服务范围及服务性质被分成六组，这种细分，我们依据的是刘和里昂于2010年的研究，他们分析了服务提供和财务业界之间的关系。

2 研究背景、方法和样本选择

在2.1节中，主要是财务报表分析的方法论和权变理论。2.2节则详细概述了给出了样本选择和附录。

2.1财务报表分析和框架

财务报表分析研究了物流服务公司当前的和未来的财务、资本和收入情况。基于其他的资源，本文的分析以年度资产负债表和当前数据为基础(弗里德森,1991)。财务报表分析可以描述和解释公司的财务情况和发展趋势(伯恩斯坦,1990)。这是一个最常见的业务分析方法，也是本文进行进一步分析的基础。

在本文中，财务报表分析的第一步对物流服务商的相关信息进行了深入的分析。公司特征以及财务信息来源于彭博社和道琼斯路透商业资讯网络数据库，使用的是基于FactSet的数据。布隆伯格以及FactSet公司是信息和财务数据的主要提供者。此外，公司公布的信息(特别是年度资产负债表)作为研究分析的一个额外的数据源。

财务报表分析的重点是关键绩效指标的测定和评价，这些能够详细的描述公司的情况。关键绩效指标可以显示公司的优势、劣势和畸变，构成了本文分析比较和评估的基础。本文中的财务报表分析，主要选择的是资产、资本、流动性和盈利能力等重点绩效指标（霍夫等1993和吉布森1982)。

2.2 样本选择和集群特征

物流服务企业集群构成，服务商选择和物流服务商的分组如下：

第一步是物流服务提供商集群的定义。物流服务商是代表其他公司进行物流活动的(德夫曼等 2012)。（声明：本译文归百度文库所有，完整译文请到百度文库。）

由于物流服务企业的服务范围不同，因此将这些企业分为六组，主要依据的是物流服务商提供的服务范围和其他相关方面因素(比如：业务关系的持续时间、集成程度等。集群企业范围为：海运、铁路、公路运输、快递、包裹运输服务物流服务商、第三方物流服务商和第四方物流服务商。

物流服务公司的集群分类依靠的是:

——提供服务的范围(查利亚等 2011; 斯蒂芬森 2006)。从基本服务：如运输和仓储(低服务范围)到增值服务(伯格伦德等1999)以及供应链协调(赫克 2001)(服务范围:广泛)。

——定制的程度。从低程度，意味着标准化产品，到高程度，意味着为客户提供一体化的解决方案(斯蒂芬森，2006；斯蒂芬森等 1999)。

——业务关系的集成程度和持续时间(拉森，2000；巴格奇和维路姆，1998；墨菲和珀尔斯特 1998)。指的是物流服务商的战略层面。企业海运、铁路、货运航空公司集群，这意味着交通运输产品的运营商的集群。这些服务也被称为基本服务，如运输或仓储。

3 物流服务商企业集群资产负债表分析

在接下来的四个部分，选择关键绩效指标KPI进行讨论。相关性的原因和清晰度，只讨论这六类物流服务集群企业。

3.1 物流服务商的资产结构

物流服务行业以资产结构为特点（阿弗里克和卡尔金斯，1994；穆勒，1993；查利亚等，2011)。在过去，物流服务商有自己的独家运输车队和仓库。可以通过公司自身的能力执行客户的订单，因此，物流服务商的大型运输和仓储资产记录都可以记载在他们的资产负债表上。（阿弗里克和卡尔金斯，1994)已经质疑资产所有权对物流服务、质量、成本和风险是否仍有真正的意义。近年来，可以观察到，物流服务商的发展不使用资产所有权。全球化背景下，物流服务企业不断追求卓越和效率，以使自身的商业模式能够适应不断变化的市场和客户的多样化要求。物流行业在过去的几十年中经历了几个阶段，这也导致了一个多样化的物流服务企业资产结构背景。

我们对物流服务商集群的分析，揭示了资产结构之间有着明显的差别。这一比较分析清楚地揭示了哪些运营商扮演着协调的角色，提供基于资产的服务。最明显的区别就是可以很明显地区分运输服务商集群和第四方物流服务商。然而航空运输公司的资产结构中，非流动资产比例较高，第四方物流服务企业的资产结构则是相反的情况。第三方物流的服务范围和包裹运输服务服务企业的服务范围，也就是说，运输服务商和第四方物流服务商，他们的资产结构也位于这两个极点之间。与第四方物流企业不同，包裹运输服务企业和第三方物流服务商可以依据自己提供运输服务，与运输公司相比，他们将运输服务和工作外包给专业的物流服务商。总之，物流服务商的资产结构揭示了物流服务商的可提供服务的程度，例如物理运输服务本身或分包

给其他物流服务商。投资强度越低，这意味着非流动资产占总资产比率就较低。资产周转率资产增加，则意味着流动资产与非流动资产的比率也增加。这表明非流动资产的周转率低于流动资产周转率。资产的投资强度也是一个灵活性指标 (投资强度越低，资产的灵活性就越大)运输公司，由于他们对运输资产的需要，其灵活性与非资产型集群相比，是比较有限的。

3.2 物流服务商的资本结构

资本结构揭示了资产融资的方式，债务或股本。(莫迪利阿尼和米勒，1958)。负债与股东权益比率是财务风险评估的主要指标(班达里，1988)。作为债务人必须保证能够为股东提供回报，与股票相比，债务资本是相对比较便宜的，但是风险更高，因为流动性不足可能会导致丧失抵押品赎回权。股票是一种给股东支付股息的更高成本形式 (诺瓦克，1995)。“债务与股本的比率将会影响股本回报率，也会影响现金流的利息和偿还债务”(克里斯托弗，2005)。