2014-34
Systemic Complexity in Integrated Thinking
Erik Bjurstom Tadanori Yosano
Ulf Johanson

Systemic Complexity in Integrated Thinking

Authors
Erik Bjurström1, Tadanori Yosano2 and Ulf Johanson3

Abstract
In this article, we set out to understand and interpret the meaning of Japanese lenders
perspective on non-financial, or soft, information of technology based small andmedium sized enterprises (SMEs) and look for its implications for the IR agenda. To
our surprise, the initial findings showed a focus on network relations, at the cost of justabout any other item of soft information about corporate strategy, organizational
structure, human resources, technologies and intellectual properties. However, a deeper
factor-analysis found a strong correlation between the different factors, revealing aholistic thinking among lenders with regard to the companies’ soft information. In otherwords, lenders have difficulties in measuring detailed soft items. In consequence, thedetails did not matter as much as the broader picture, in which detailed measures ofdifferent items were interpreted through the firms’ credibility, revealed by their network
relations. We further conceptually generalized this insight as an expression of theconcrete character of the business reality of the companies, as interpreted through thelender-borrower relationship.

Key words
Integrated Reporting, Integrated Thinking, Network, Lender-borrower relationship,
SME’s, Industry strategies

1

School of Innovation, Design and Technology, Märlardalen University, Eskilstuna, Sweden.
Graduate School of Business Administration of Kobe University, Kobe, Japan3
School of Sustainable Development of Society and Technology, Märlardalen University, Västerås,Sweden.

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1. Introduction
There is an increasing sense of urgency to restore confidence in businesses through theestablishment of integrated reporting (IR). However, while the need for improvement can hardly bedenied, there is a risk that this urgency makes us overlook fundamental challenges to the project toprovide a clear and concise representation that reflects the commercial, social and environmental
context within which the company operates. As our example will show, there is an evident risk tounderestimate the complexity of such a task. While integrated thinking is needed to understand therelationships involved in the value creation process, the greatest challenge involved may be tounderstand the very character of those relationships, even when only considering the perhaps mostnarrow conception of IR in the most traditional contexts, namely lenders’ perception of valuable
non-financial information about technology based manufacturing companies. Acknowledging thefull range of stakeholders and dimensions that would need to be involved in a more full account of
the company’s impact and responsibility in society legitimately adds further complexity to thischallenge. Notwithstanding, society can hardly afford a failure of IR. However, in order to be
successful, we believe that considering the very character of the relations in any representation of
the business reality is crucial for building a strong conceptual basis for IR.
The idea of creating a connectivity of information indeed lies at heart of the IR agenda. However, as
we are going to emphasize, this connectivity of information must in turn go beyond the surface ofrepresentation in order to create an understanding of the underlying relationships in the value
creating process in terms of the very character of those relationships. As our findings point out, thekind of relationships that are increasingly relevant already in traditional technology based
manufacturing industry are those of interactive systemic complexity, rather than of simple, linear
logics. Such relationships are even more relevant for describing service and knowledge intensive
work. Consequently, we argue that the integrated thinking able to promote IR as a successful future
standard vehicle for reporting must emphasize the interactive systemic complexity characteristic forvalue creation processes even in the eyes of the most traditional stakeholders, the lenders, and inrespect to even the most traditional industries. This notion goes against the grain with mostestablished thinking in economics and reporting expressed e.g. through notions of the production
function of the firm.
In this article, we set out to understand and interpret the meaning of Japanese lenders perspective on
non-financial, or soft, information of technology based small and medium sized enterprises (SMEs)
and look for its implications for the IR agenda. To our surprise, the initial findings showed a focus
on network relations, at the cost of just about any other item of soft information about corporate
strategy, organizational structure, human resources, technologies and intellectual properties.
However, a deeper factor-analysis found a strong correlation between the different factors,
revealing a holistic thinking among lenders with regard to the companies’ soft information. In otherwords, lenders have difficulties in measuring detailed soft items. In consequence, the details did not
matter as much as the broader picture, in which detailed measures of different items wereinterpreted through the firms’ credibility, revealed by their network relations. We further
conceptually generalized this insight as an expression of the concrete character of the businessreality of the companies, as interpreted through the lender-borrower relationship.

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We draw the conclusion that in order to become a useful tool in restoring confidence in business, IR
has not only to make the intended move from a systematic to a systemic view, through integrated
thinking reflected in the connectivity of integrated reports. Instead, the systemic view also needs tomove away from simple and linear logics of notions of production functions or value chains in its
view on value creating processes and quite contrary assume interactive systemic complexities asincreasingly being the normal case in business. We build up our argument by first reviewing themove of IR from a systematic into a more systemic view on business and its reporting. We
thereafter present the empirical findings from the Japanese Ministry of Economy, Trade andIndustry’s (METI) survey of 336 lenders judging the value of soft information of technology based
manufacturing SMEs. In the following chapter we extend our analysis with the aim of conceptual
generalization of the empirical findings. Finally, we discuss our conclusions and their possible
implications for the future IR agenda.

2.

Integrated thinking: towards a systemic view

IR is essentially a process of communication, however most visible in the establishment of periodic
integrated reports about a company’s value creation over time. Not least important is the idea of
integration of different aspects of a firm’s activities in relation to a broad range of stakeholders. A
key feature for realizing the concept of IR is the notion of integrated thinking, thought of as anability of an organization to understand the relationships between its organizational units, capitals
and effects. The basic notion is to move away from ‘silo thinking’ and instead establish an accountof the connectivity and interdependence of a full range of factors affecting the company’s value
creation in the eyes of a broad range of stakeholders. In the practical considerations of how toestablish such reports, such communication procedures and such integrated thinking issues ofreporting boundaries and the optimal level of aggregation and information loads soon become
critical. In a broad sense, the ambitions of integration, connectivity and reconsideration oforganizational borders marks a move away from the traditional systematic focus of accounting,sorting everything into a classification apparatus not even remotely resembling the value creating
activities and processes out in the real world, towards a more systemic ambition to depict thecomponents and relations involved in creating the value that constitutes an organization’s raisond’être.
While attempts are being made as to break accounting’s tradition of ignoring the systemic realities
of value creation for the sake of systematic order and notions of accountability as delimited byorganizational silos, it is hard to break out of a long tradition immediately. Striking examples are
the illustrations below that can be found in the prototype framework of IR. While these generaldescriptions by necessity will tend to lack any specificity and detail, the point here is that the eventhough efforts are made to approach the value creating realities of real life processes, their depictionin IR frameworks barely break out of the accounting tradition of emphasizing orderly classification
rather than models that illustrate any flow or interaction creating the value accounted for in thereports. Hence, it is striking that even the illustrations of IR try to demonstrate such flows by seeing
the organization and its business model in terms an input-output model in practice only balance
between this attempts to a systemic description and the more traditional approach to simply classify
and list different items of assumed importance. In other words, the first two illustrations of the IR
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framework are in practice little more than a clssification of different capitals relevant asorganizational inputs and outputs, or a classification of things relevant for the firms business model.

Figure 1 ”The organization”, from the IR prototype framework p. 8, www.theiirc.org

Figure 2 ”The business model”, from the IR prototype framework p. 9, www.theiirc.org
While systemic descriptions can be expected to be much more specific on a company level, andeven better on a business unit level, the issue of becoming truly systemic in the view of anorganization has further implications than only pointing out directions of flows and assumed
causalities between different events in the interplay between actors, resources and activities. In thedebate, most voices agree with the ambition towards more integrated or systemic views on a4

company’s activities. However, the very character of such relations has not been sufficiently
debated. Rather, for accounting scholars, notions of value creation processes are often swiftly
converted in to notions of the production function, i.e. mathematically simulating its logic, or more
simple and linear illustrations of the successive adding of value in different steps in a value chain
analysis.

Figure 3 ”The value chain”, from the IR prototype framework p. 14, www.theiirc.org
The problem with this view is that the notion of a systemic view more or less automatically retorts
to a point of reference which is in increasingly irrelevant: the simple and linear logic of thetechnologically buffered and pretended closed, vertically integrated and hierarchically controlled
production system of the heydays of mass production (c.f. Chandler, 1977; Womack et al. 1990).
Hence, such a notion of connectivity and relationships between different items and factors of thevalue creating process may increasingly seem outdated in relation to other views emphasizing abroader range of production technologies ranging from the simple to those characterized by inherent
unpredictability as a consequence of interactive complexity.
An often cited reference for this argument is Thomson’s (2003[1967]) distinction between pooled,sequential and reciprocal interdependencies in the production technology, where different units
work independently, in distinct steps of the value chain, or where units are mutually dependent oneach other’s output. These different logics of production, or value creation, give rise to threefundamentally different logics in their production technology: a mediating technology where units
operate independently, long-linked technology which is typical for traditional serial industrial
production, and intensive technology where units work together intimately. Perrow (1984) further
developed the argument that while traditional industrial production follows a more linear logic,
multi-goal agencies and knowledge intensive work show much more complex and thereby
unpredictable patterns of interaction in the production process. Later suggestions have emphasized
the need to look at not least service production in terms of value constellations, where actors come5

together simultaneously to create maximum value in a more flexible manner at a given moment,
rather than as value chains of stable and predictable interaction (c.f. Normann & Ramírez, 1998).
This kind of networking logic can also increasingly be observed in today’s manufacturing industry.
Karlsson (2003) pointed at the new tendencies of a network approach in manufacturing companies’
strategies for industrial system design for the coordination of actors, activities and resources. Hence,the perspective of these strategies are rather from a knowledge based view of strategy, not focusing
on the boundaries of the formal organization, but instead emphasizing the flows and structures
relevant from a value creating logic. Both globalization and technological development driving
automation and information economics are important drivers for this development. The flexibilityof the production system facilitates mass customization, in turn eroding established borders between
different markets and segments with far reaching consequences both for strategy and operations
management. In combination with new distribution systems and business models challenging
dominant actors in established markets and niches, the playing field is changing in profound ways.
In response to such pressure, large organizations increasingly disintegrate their production systemand formal structures to match the flexibility and pace of technological development of newcompetitors. By experimenting with network arrangements as a somatic response to uncertainty (c.f.
Baumard, 2002) vertical integration (c.f. Chandler, 1977) is abandoned for more flexible
collaboration with suppliers typical for Japanese manufacturing systems (c.f. Womack et al., 1990).
Increasingly, large companies focusing on selling end-products to customer become specialized
systems integrators, moving away from the product level to focus on functions that create customer
value, making more and more complex offerings rather than managing lower levels of technology.
Thus, the core competence of the systems integrator becomes horizontal, focusing on functions andproduct characteristics that are more directly related to customer value. As a result, industries are
increasingly relying on external resources and actors for achieving competitiveness. Hence, there
are good reasons for addressing the fundamental question of what a systemic notion of integrated
thinking would mean.

3. Representing Value Creation
This case study is based on an extensive survey among Japanese lenders concerning what
information that is deemed critical and relevant for doing credits decisions among technology-based
SME’s in Japan. The ultimate reason behind this investigation was the double interest of theJapanese government to increase efficiency in lending decisions as well as re-establishing trust in
the financial sector. One of the key players in these efforts is the Ministry of Economy, Trade, andIndustry (METI), e.g. by striving to strengthen information transference between firms andstakeholders.
Before the 1980’s, the Japanese lender-borrower relationship lending was characterized bylongevity. This would change after the middle of the 1980’s when Japan would enter into a bubble
economy. While lenders depended on the economic value of land holdings and real estate todetermine trustworthiness when lending money to borrowers, this philosophy will be a myth as land
and real estate values keep appreciating. The bubble economy turned in a similar fashion as the U.S.
real estate collapse. After this Japanese financial, land value, and real estate crash in the early6

1990’s, Japan was forced to shift toward another style of securing lending relationships andbuilding trustworthiness. This new method relies more on hard, or financial, information andlending is now to a larger extent based on finance theory consistent with a more typical Western
financial perspective. The shift led to two market reactions: 1) high competition between lenders,and 2) low profitability. The lenders’ heavy reliance on financial figures limited the advantages
between lenders, and high competition meant that not all firms would be able to survive. In theefforts to counteract this market reaction, the Japanese Financial Service Agency (FSA) introduced
an action program that was intended to help all lenders survive the harsh market conditions. The“Program for strengthening Relationship Banking Function,” introduced in March 2003, enhanced
the lender’s ability to judge a borrower’s trustworthiness using soft information (Yosano andNakaoka, 2011a). While the FSA works to strengthen lending relationships METI on the other hand,focuses on soft information.
Soft information includes the corporate strategy, technology, intellectual property, human resources,and networks. All of these factors are seen as promising engines for lenders, and the efforts of the
METI to promote the utilization and transference of these factors is actually supportive of the
FSA’s relationship lending action program (c.f. Yosano and Nakaoka, 2011a). Hard information
generally involves a corporate financial track record and historically accumulated resources.
However, the company is alive and under constant change, therefore, the company should act onreal social circumstances according to their corporate strategy. Soft information is able to transformthe actual corporate figures into a realistic picture of the borrower’s trustworthiness. However, wecannot access soft information directly, because they are naturally, by definition, intangible.
Nevertheless, if lenders want to judge a corporation’s true trustworthiness, they need a way toevaluate the realistic picture. METI’s initiative4 can motivate us to find the way to judge the actual
corporate trustworthiness using soft information as studied in this paper.
We are motivated to see the realistic image of the corporation’s business by studying their soft
information. With thanks to the METI initiative, we were able to access survey questionnaire data,
and analyze how lenders use soft information to create trustworthiness with the borrower. The
METI set up a research committee that focused on "investigating and researching credit
technologies that utilize evaluation corporate technologies" in the 2008 fiscal year. Before sending
questionnaires to lending institutions, committee members first discussed which items are
representative of corporate technologies involving intellectual properties, networks, organizations,as well as corporate technological strategies. This list of items was in reference to interview surveys
from 6 regional and cooperative banks conducted by the SMRJ (The Organization for Small and4

The METI encouraged small businesses to disclose supplemental, non-financial information that could be used
to determine the potential for growth and/or sustainability, and to eliminate information barriers for raising funds(Holland and Johanson, 2003). Following this example, the “Organization for Small and Medium Enterprises andRegional Innovation, Japan” (SMRJ), who is an affiliated association of METI, issued The Manual for SME
Intellectual Capital Reporting in March 2007. This manual focuses on the specific concerns of small businesses.
Non-financial information could further help convince lenders of the small businesses’ trustworthiness when they
provided IC Reports. This trend is a complete contrast from the “Guideline for disclosing Intellectual Assets
Based Management” (GIABM) that focuses on big businesses as illustrated in detail by Sumita (2008) andJohanson et al. (2009). In fact, the number of small business disclosures has increased from thirteen in the 2006
fiscal year to sixty in the 2008 fiscal year. While sixty is a small number, it still reflects a dramatic increase over a
two year period.
7Medium Enterprises and Regional Innovation, Japan) in late 2007 (Yosano and Koga, 2008,
Yosano and Nakaoka, 2011b).
3.1 Sample and Methodology
Our study focuses on the lenders’ development of trustworthiness by utilizing soft information, andtherefore, our study sample involves a total of 336 lenders: 4 Mega Banks, 85 Tier I and II regionalbanks, and 247 cooperative banks.
We used five general factors to conceptualize the notion of soft information: corporate strategy,
technology, organizational structure, networks and human resources. These were in turnoperationalized in more specific items. Table 1 shows the respective utilization level of soft
information for creating trustworthiness during the lending process. 1 = "No usage level," 2 ="Weak Usage level," 3 = "Medium Usage level," 4 = "Strong Usage level," 5 = "Extremely Strong
Usage level."
The results are shown in Table 1 and found on the Likert scale that measures credit decider attitudes
toward usage, divided into five factors and a total of 65 items (all of these factors and items areshown in Table 1.). The elevated cronbach alpha categorical factor indicates high internalconsistency of the model:- 5 corporate strategy items were combined into one corporate strategy factor (cronbach alpha5= 0.9007)- 9 organizational structure items were combined into one organizational structure factor(cronbach alpha = 0.8776)- 3 employee items were combined into one human resource factor (cronbach alpha = 0.9751)- 23 technological and intellectual property items were combined into one technology factor(cronbach alpha = 0.9740)- 15 network items were combined into one network factor (cronbach alpha = 0.9452)
A remark of general importance to understand the results is that a low score does not necessarilymean that an item is useless or unimportant for a company’s vale creation. Rather, it indicates that
this factor is of limited value for lenders as they may be hard to judge, i.e. the information value islow. As such, the results rather point at the accessibility of reliable soft information. However, froma lender’s perspective, abstract speculation will sooner or later materialize in concrete outcomes,
which creates incentives to judge more carefully the information value of different items andthereby also the overarching factors. A general conclusion of this descriptive analysis is that almost
all the soft factors seemed more or less difficult to access and judge, with the exception of network
relations. Furthermore, many of the most acknowledged items in the debate about intangible
resources seemed hard to use as factual underpinning of credit decisions.
For instance, while corporate strategy is made into the backbone of many intangible as well as
tangible frameworks (c.f. MERITUM, 2002; Kaplan & Norton, 2001), this factor as a whole5

Cronbach alpha is a coefficient for reliability. It is commonly used to measure the internalconsistency or reliability of a psychometric test score for a sample of examinees. Here, for example,
0.9007 means that over 90% of the examinees in our sample, who are representative of lenders,consider our corporate strategy category, containing 5 soft items, as a primary factor.
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showed to be of very limited value for credit decisions (mean value = 2.84). Not least surprising
was the finding that while intellectual properties in general is seen as one of the most reliable soft
indicators, the item “Whether the firms utilize their intellectual properties strategically” did scorevery poorly in the eyes of the lenders. On the other hand, items like “Whether the firms make themost of their uniqueness and specialties in technology when outlining their business plan” and“Management comprehension of technology” showed to be more, albeit not excessively, useful.
The usefulness of items under the factor of organization structure might be even more disappointing
reading (mean value = 2.56). At the bottom of the list, the information value of “security systems
to prevent technology leaks” and “incentive system for an invention” showed to be of very limited
value. Remarkably, even the highest ranked items under this factor, namely “technology conformity
to the market demands” and “the use of quality management systems” did not stand out as very
useful. On the other hand, public recognition through “public grant and/or awards” showedsurprisingly useful for judging credit decisions.
While it logically may seem impossible to dismiss the role of human resources for firm’s future
success, the lenders judgment of this factor is a somewhat depressive reading (mean value = 2.52),
if not for the sake of human resources, then for the sake of rationality. Neither “expertise”,“knowledge, morale and motivation”, nor “qualified employees” showed any greater
trustworthiness in the eyes of the lenders. In similar vein, within the technology factor (mean value= 2.40), the only item scoring above the middle of the scale was the “superiority” of present
technology over comparable products or technological areas, while items like the possibility of“commercialization”, the likelihood of “imitation” and the dependence on “expertise” were ranked
at the bottom of the scale. Confirming this pattern, the view on intellectual properties was
somewhat positive only in terms of the mere “number of patents”, while its relation to the “core”,“surrounding patents” or “economic value” of unused patents was deemed to be of very limited
value for credit decisions. Summing up, the factors of human resources, technology and intellectual
properties were seen as unreliable for credit decisions as were organizational structure and strategy.
In stark contrast to the above findings, the networks factor (mean value = 3.12) stood out as themost important one for lenders’ ability to use soft information for their credit decision. While partly
containing low-ranked items like the “coordination” with other firms, the networks-factor generally
showed to be the most useful one. The most high-ranked items in the whole questionnaire were
“The support system of specialists, such as lawyers, patent agencies and consultant engineers” and“Whether the firm has already captured the target market”. In a broader sense, indications of good
network connections with other lenders, equity holders, universities and public (government)
research institutes etc. was deemed as useful information for credit decisions.
While the above descriptive analysis of single items and factors may be interesting reading, theresults may also raise further questions about the actual message behind the results: do lenders
really ignore all but network information and to some extent strategy information, or are there
further insights to be gained from the internal correlation between different factors? To answer
these questions the material presented in Table 1 was later further investigated by looking at thelatent factor behind soft items in the following section.

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Table 1 ”Lenders’ usage of soft information”

Corporate Strategy(mean value = 2.84)

Mean Value

Standard Deviation

Whether the firms make the most of
their uniqueness and specialties intechnology when outlining theirbusiness plan.

3.16710.7416

Whether the firms utilize theirintellectual properties strategically.

2.55940.7254

Whether a complete switch of
products/services is needed with the
adoption of technologies.

2.86960.7415

Clarify and improve corporate
revenue by utilizing technologies
and intellectual property.

2.58600.6950Management
technology.

3.25290.7578comprehensionofCronbach Alpha = 0.9007

Completion of R&D equipment.

2.77780.7486

Brand power or profit margin, basedon the high level of technology.

2.8596

0.7834Training program for technology
department employees.

2.38010.6947

Technology conformity
market demands.

2.9912

0.7914The use of the quality management
system (ISO, etc).

2.93290.7521

Systematized, and/or visualized
know-how(The
Organization Stracture technological(mean value = 2.56) construction of a database, thespread of an employee training
manual, etc).

2.28740.7232The construction of security systems
to prevent technology leaks (Thesecurity management, etc).

2.13130.7115

Actual results of the public grant
and/or awards.

2.88050.7800

Incentive system for an invention(salary, bonus, and personnel
evaluation, etc).

2.18480.7619tothe

Cronbach Alpha = 0.8776

Human Resource(mean value = 2.52)

The expertise and experience levelof senior workers and the rank andfile in the engineering and/or
strategic planning department.

2.6531

0.7831The explicit and implicit knowledge,
morale, and motivation of senior andjunior workers in the engineering
and/or planning department.

2.47970.8079Qualified employees.

2.56520.7209Cronbach Alpha =0.9751

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Undefended technologicalhow (business secret).

2.40520.8177The superiority over other same
products and/or technological areas.

3.05540.8549The level of barriers for new entry.

2.62100.8106

The product life cycle (The period
which the product produces therevenues).

2.61810.7854

Innovation of core technologies.

2.65500.87202.6696

0.8418The functional superiority of thetechnologies.

2.68620.8633The possibility of expanding theapplication of the core technology
and business model.

2.52050.8343

Time
frame
when
the
product/service (which is based on
the technologies) will find its
market.

2.53100.8148The possibility of product/service
commercialization which is based on
the core technology and businessmodel.

2.41640.8382

Whether the core technology iseasily copied or imitated.

2.36950.8251

Whether the core technology isheavily dependent on the specificqualified expertise.

2.37240.8184

The relationship between the coretechnology
andsurrounding
technologies.

2.50290.8001

The number of patents.

2.76680.8260The number of annual applicants
and/or legislative patents.

2.32650.7636

The actual results of licensees.

2.33430.7608The economic value of the patents.

2.32750.7529The patent portfolio for the product.

2.15590.7179Whether the patent is core or close
to core.

2.09090.7158Whether the core patent needs
application for the surrounding
patents.

2.04970.7022

Whether the patent is easily copiedor imitated.

2.11990.7145

Whether the patent is heavily
dependent on the specific qualifying
expertise.

2.16670.7133The economic value of the unused
patents.

2.01750.7344The price superiority
technologies.

Technilogies

andIntellectual Propeties(mean value = 2.40)

know-

of

core

Cronbach Alpha = 0.9740

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Networks(mean value = 3.12)

The relationship with retailers (retailsellers and wholesalers).

3.62500.8128Whether the firm has already captured
the target market.

3.75940.8195

Small customer base (Whether thefirm relies exclusively on a small
number customers).

3.35360.8227

Whether the relationship withexisting customers is regular or
irregular.

3.39420.8325

Coordination with the developers
and engineering firms.

2.64810.7855

Coordination with the
product/service design firms.

2.64810.7742

Coordination with the manufacturingfirms.

2.61580.7085

The relationship with suppliers.

2.72810.7990Collaboration regarding researchwithin the firms.

2.78430.7610Collaboration regarding distribution
within the firms.

2.73100.7644

Collaboration regarding researchwith universities and public(government) research institutes.

3.05800.7717The support system of specialists,such as lawyers, patent agencies, andconsultant engineers.

3.83530.9035

The relationship with government
and municipal offices.

2.85130.9450

The relationship with other lenders.

3.66760.8761

The relationship with equity holders.

3.69280.8481

Cronbach Alpha = 0.9452

3.2 Methodologies and factor analysis results
We conducted factor analysis in order to investigate the correlation between the five factors. As thefive factors have different numbers of underlying items, we cannot check the correlation between
the five factors directly. Instead, we extract latent factors and investigate the correlation between
latent factors. The corporate strategy factor has a primary factor whose eigenvalue6 is 2.41299 andto a 0.8043 proportion7. The organizational structure factor has a primary factor whose eigenvalueis 5.04378 to a 0.5604 proportion. The human resource factor has a primary factor whose
6

Eigenvalue measures the variance between all the variables that are accounted for within a factor.
Proportion shows the degree to which a primary factor variance can explain the variance of all theindividual variables.
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eigenvalue is 2.41299 to a 0.8043 proportion. The technology factor has a primary factor whose
eigenvalue is 9.63748 to a 0.7413 proportion. Lastly, the network factor has a primary factor whose
eigenvalue is 8.57670 to a 0.5718 proportion. Hence, the primary corporate strategy factor’svariance explains over 80% of all five items’ variance.
Table 2 Correlation Matrix
Corporate Strategy

Corporate Strategy

Organizational
Structure

Human Resource

Technology andIntellectual Properties

Networks

0.7764

0.59360.74810.62690.64120.80620.5981

0.66160.5504

Organizational
Structure

0.7659Human Resource

0.60010.6199Technology andIntellectual Properties

0.74460.80220.6674

Networks

0.61750.62610.51030.65900.6655The lower left part shows Pearson's coefficients and the upper right part shows Spearman's coefficients.

Internally, within the corporation, the correlation between the organizational structure factor and thehuman resource factor is 0.6199*** 8 (Pearson’s coefficient), the correlation between theorganizational structure and the technology factor is 0.8022***, the correlation between the humanresources factor and the technology factor is 0.6674***.
Between the corporation and its boundary networks, such as suppliers, customers, R&D codevelopers, and government and municipal offices, the correlation between the organizational
structure factor and the network factor is 0.6261***. The correlation between the human resource
factor and the network factor is 0.5103***, and the correlation between the technology factor andthe network factor is 0.6655***. We are able to address that the latent factors within the corporation,
especially for SMEs, are highly correlated with the boundary network factor (1% significance level).
In other words, in the eyes of the lenders, the trustworthiness of internal corporate information isstrongly related to indications of the company’s network relations.
Last, we combined three primary factors: the organizational structure factor, the human resources
factor, and the technology factor into one primary internal corporate factor. We found that thiscomprehensive factor has a 2.40409 eigenvalue to a 0.8014 proportion.

8*** denotes 1% significance level for the rejection of the null hypothesis: the organizational
structure factor is equal to the human resource factor.
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Because of the critical importance of the relation between corporate strategy and corporate
resources, we would like to sketch the relationship between the corporate strategy and internal
corporate resources in addition to boundary organizations or networks.
The correlation between the corporate strategy and the boundary network factor is 0.6175***, andthe correlation between the corporate strategy and the primary internal corporate factor is0.8123***. The internal corporate and boundary factors are highly correlated with the corporate
strategy factor (1% significance level). With this data, we are able to suggest that lending practices
definitely notice the relationship between the corporate strategy and the internal corporate andboundary network latent factors.
This tells us that the lenders have difficulties in judging internal resources as well as corporate
strategy as isolated data. However, network information is tightly correlated with both internal
resources and strategy. This shows us that lenders manage to judge corporate value creation byusing network information to put other data into a context in terms of the company’s relation toother businesses and the rest of society. In other words, lenders tend to apply a holistic view in theirapproach to estimate any single company’s value creation. This does not mean that the single
measures are uninteresting, just that no single measure is revealing the entire or critical insights
needed to make a credit judgment.

4. Analysis
Our empirical investigation into lenders perception of the value of soft information about
technology based SMEs showed that the context in terms of network relations was decisive for
credit judgment. In other words, it was the broad picture of the company’s relation with otherbusinesses and the rest of society that provided credibility to the firm and to all other information
about its operations and assets. We called this a holistic view on the companies’ value creation. One
way of expressing the idea of holism is to say that it is the broad picture of all measures, or rather
their relation to the companies’ network relations and strategy that builds up a credible picture in
the eyes of lenders. This means a shift of focus from the much debated ability for reliablemeasurement of soft items into a focus on the totality of measurements, or – to be more exact – to afocus on the relation between measurements, rather than on the single measurements themselves.
These findings may inspire the notion of integrated thinking by highlighting the move from asystematic view, which puts the classification of single measurements in focus, to a systemic view
more emphasizing the interaction between different items and factors involved in a company’svalue creation. However, the holistic thinking shown by lenders in our case may not only reveal an
attitude towards measurements, but might also reflect the material underlying business reality forJapanese technology based SMEs which may be equally important as inspiration for thedevelopment of the emerging IR agenda. Hence, integrated thinking should not only reflect theambitions to integrate reporting into a more comprehensive view of the company, but must
ultimately reflect the realities of the very value-creation process itself. In consequence, the movefrom a systematic focus on classification of resources, liabilities, income and costs to a modeling of
the value creation process itself needs to be problematized in terms of the very characteristics of14

such value creating realities, which may go beyond shallow notions of production functions andvalue added analyses. Indeed, we have good reasons to believe that the value creation logic in aknowledge society may be of much more complex and messy nature than often assumed inovergeneralized accounts of strategies and processes of value creation. As our example shows, thismore complex notion of systemic thinking – taking into account the typically systemic interactive
complexities – may be increasingly relevant even in the most traditional settings of technology
based industry.
While the kind of holistic, complex systemic thinking illustrated in our findings may be typical offor a more eastern mindset (Bjurström, 2012), there is also strong reasons to believe that this not
only reflects a cultural component, but that it is also founded in a networking business reality that isincreasingly also relevant globally.
As Karlsson (2003) showed, prevalent strategies for companies’ industrial system design isincreasingly taking on a network approach, choosing not to focus on the boundaries of the formalorganization, but instead emphasizes the flows and structures relevant from a value creating
perspective. Consequently, the most important thing is not whether or not value is added within theown firm or in collaboration with others, but to map and understand what actors, resources andactivities that interact within and around the formal organizational entities to achieve valuable
solutions for customers and stakeholders. The flexibility of such manufacturing systems
increasingly emphasizes mass-customization which in turn erodes neat classifications of market
segment while at the same time having important influences on operations management.
Globalization and technological development driving automation and information economics arechanging the playing field, together with the generation of new distribution systems and businessmodels increasingly challenging established markets, niches and big companies.
Under such circumstances, many companies not only take on a network perspective as an analytical
tool to understand their value creating processes, but also tend to disintegrate their formal structures
to increase flexibility and adaptiveness. Indeed, networking arrangements may be seen as a somatic
response in the face of uncertainty (c.f. Baumard, 2002). The abandonment of the classical notion ofvertical integration into large companies (c.f. Chandler, 1977) is undeniably a characteristic trait ofJapanese manufacturing systems (c.f. Womack et al., 1990). However, in the more competitive
global environment, companies move from the product level and are increasingly rather selling
functions that create customer value, not least by opting at making more complex offerings,
focusing on systems integration rather than on lower levels of technology. In consequence, the corecompetence of systems integrators becomes more horizontal, focusing on product characteristics.
As a result, more and more industries are relying on external resources and actors for achieving
competitiveness.
This new, and to some extent typically Japanese industrial structure, sheds further light on ourempirical findings in the sense that the holistic thinking shown by lenders may not only reflect
cultural tendencies of non-atomistic thinking, but rather reflects globally emerging business realities
with a long history in the Japanese context. In other words, the rationality behind Japanese lenders
skepticism towards single soft information – with network relations as an exception – may lie not
only in the thinking but in the very structure of the production system itself: if you are not able to15

maintain well functioning network relations, the value of your assets may also be questioned. On
the other hand, while the reliability of measurements of soft information may be questionable, thefact of having well functioning network relations may provide the reliability of the company as awhole – including its claims of competence etc – by demonstrating a strong position in the
networked production system.
The picture that emerges and is reflected in the lenders perception of soft information is one of
dynamism beyond notions of production functions and stability in buffered productions systems
through vertical integration in formal hierarchies producing standardized products meeting a stablemass market demand like in the heydays of traditional industrial production (c.f. Womack et al.,1990). Hence, at least in such a business environment, integrated thinking has to go beyond
assumptions of stability as a basic feature of the production system reflected in the reporting. Rather,as Weick & Sutcliffe (2007) put it, stability must be seen as a dynamic non-event. Likewise, if
stability is obtained even in the most turbulent industries, it must be seen as a dynamic struggle tokeep up the varying and ever changing needs of customers and stakeholders in harsh competition
with both established actors and new constellations continuously reinventing themselves totranscend the borders between markets and segments. From this perspective, the frame of reference
for talking about integrated thinking does not much resemble the typical assumptions of stability
and aggregation of information of the company as one integrated and isolated being, typicallyreflected in economic notion of the production function. Stability is no longer a function ofvertically integrating operations into production systems under hierarchical order. Instead, insofar
stability is temporally achieved, it is only through the diminishing the pace by which your relations
with customers and stakeholders erode (c.f. Williams, 1999).
The consequences for the IR agenda not least concerns the very meaning of integrated thinking. In
our view, integrated thinking must take into account not only the integration of different kinds ofdata in the reporting, but above all account for the very character of the business reality supposed tobe reflected in the IR. A move from systematic thinking in terms of mere classifications must be
extended not only to systemic thinking in terms of linear models of the business process or value
creation, but also take seriously the systemic complexities present in many production systems,
even in the most traditional industries as accounted for in this example. The most criticalconsequence of the interactive, systemic complexity is the unpredictability of interactions in the
production process, so typical for knowledge intense work (c.f. Perrow, 1984), but also increasingly
present even in traditional technology based manufacturing industry.
Of immediate importance for the notion of integrated thinking is the very point of reference for the
logic of value creation. While an aggregated production function would emphasize the mean valuesof underlying data and ignore variations in the logic, the real life value creation process isincreasingly leaving the logic of pretended closed systems and instead value creation instead to anincreasing extent stems from the very ability of flexible adaptation to diverse and varying needs.
This open systems reality of present day production systems also means an emphasis – rather thanan ignorance – on the dimension of temporality, not least through notions of just-in-time production
and more contingent and time limited cooperation in projects and joint ventures etc. This also
increasingly means an unpredictability of the patterns of interaction. However, while this logic
relies more on market solutions than on hierarchical order, successful interactions tend to be16

repeated, shaping patterns of interaction ultimately re-creating a structural order in terms of ongoingand potential future interactions in networks. These networks may well show to be rather stable
over time, which is often the rule in the Japanese context. However, the strengths of these ties andtheir following stability do not rely on any contractual or hierarchical arrangements as much as they
rely on earlier evidence of successful collaboration shaping efficient routines and expectations forthe ability of common future efforts to combine knowledge and capacities to meet varying customer
needs. In other words, rather than permanence, ongoing adaptation is what shapes value creatingprocesses and structures over time.
Summing up, we may ask whether the IR agenda does not miss the point of prevalent trends
towards increasing complexity in business life by reducing integrated thinking to a notion of
production function representing value creation. In a more dynamic world, looking at network
connections would tell more about a firm’s ability to adapt and keep itself sustainably relevant overtime, than only looking at the internal and pretended closed production system of traditional
manufacturing industry. With reference to our study, where lenders tended to emphasize the broad
picture in a holistic way rather than focusing on details of singular measurements, we may ask
whether the discussion about too much or too little information i.e. the level of aggregation, does
not breed the notion of linear, non-complex structures where information problems can solved by
reductionism rather than a holistic thinking more compatible with the systemic complexities anduncertainties characteristic of real world production systems. Furthermore, following a systemic
view, a network perspective would be more likely to reveal how real world value creation processes
work over both internal and external organizational borders. Consequently, integrated thinking must
be extended to incorporate holistic notions of systems of interactive complexity, uncertainty andnetworked value creation processes over formal organizational borders.

5. Discussion
In this article, we set out to understand and interpret the meaning of Japanese lenders perspective on
soft information of technology based SMEs to inspire conclusions relevant for developing the
emergent IR agenda. The outcomes emphasizing the role of network relations for assessing thetrustworthiness of all other information led us to conclude that the holistic thinking among lenders
was the main finding of the study. We further conceptually generalized how this preference towards
holism and emphasis on network relations also for the trustworthiness of other factors may reflect
the material logic of a more distributed production system, with larger companies increasingly
disintegrating in order to focus on horizontal technologies and establishing network relations withsmaller firms. This led us to draw the conclusion that while being a typical trait of eastern mindsets,
the focus on holism and network relations may not only be valid in the Japanese cultural context,
but could also reflect the ongoing global trend towards outsourcing and establishment of more
flexible network structures. Consequently, we speculate that the view of Japanese lenders might begenerally useful for developing and specifying the notion of integrated thinking, as to take into
account the prevalent complexity and unpredictability as well as flexibility as a key factor in value
creation.
One of the most fundamental consequences for this view is that the point of reference for value
17

creation changes with the networked logics of production. A common debate about IR as well asother suggestions for reporting is what should be the relevant level of information provided: either it
seems to be seen as too little or too much information. We suggest that a more specific question
would be what kind of information that should be disclosed is more a matter of the logics of the
production system. In our view, this would be the very essence of integrated thinking. Hence, rather
than assuming that a linear and simple logic of value creation, sometimes expressed through thenotion of a production function, is generally valid, the first and most important question for IR
should be what kind of logic that dominated that business to be accounted and how it should be
represented to contribute to an understanding of the character of the relationships between different
actors, resources and activities. In traditionally stable production systems with a buffered andseemingly closed production system in a vertically integrated and hierarchically controlled company,
the linearity of the production process provided simplicity and predictability allowing for
reductionism in its representation. However, the uncertainties would rather emerge at the end of theline, where products and services have to meet customer needs. A networked dynamic production
system rather turns this logic around. While its interactive systemic complexity generates
uncertainties and unpredictability in the logic of production, its relevance and value is instead
continuously demonstrated through persistent network relations with other companies and with thesociety at large.
In our view, the suggestion of integrated thinking as an expression of interactive, systemic
complexity also has consequences for the very aim of the IR agenda. If IR is going to meansomething more than connectivity of information in terms of a change in the structure ofpresentation and go beyond the surface of representation it also has to create understanding of theunderlying relationships in the value creating process. This is a claim that most proponents of IR
can agree upon. However, our main claim is that if IR is going to live up to its ambition to create
and understanding of relevant relationships, it fist has to create an understanding of the very
character of those relationships. While our Japanese case study may reflect a cultural element ofemphasizing interactive complexity, leading to a holistic thinking, the sample chosen for our study
at the same time reflects one of the most traditional branches i.e. technology based manufacturing.
If such conservative production systems already demonstrate that kind of interactive complexity,
uncertainty and network logic, it is plausible that our conclusions will be even more relevant forservice industries and knowledge intense work, both of which are growing in size and importance.
Therefore, the integrated thinking able to make IR an efficient tool for lenders must emphasize theinteractive systemic complexity inherent in prevalent value creating processes. And if nothing else,
adding multiple perspectives and systems of meaning of relevant stakeholders will make sure that
notions of complexity will rather seem like understatements.

18

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