Con guring Value Networks based on Sub jective Business Values

Abstract

Monetary pro tability is an objective value essential to the sustainability of a value network. The analysis of this requirement continues to receive substantial attention by the e3value research community thus far. However, subjective values such as privacy, security and trust might also play a key role on the con guration of a value network, especially when it is necessary to di erentiate equivalent monetary value propositions. This paper describes an ontological proposition for con guring value networks based on subjective values. The ontology is aimed to be used as complement of the e3value framework, blending concepts of Multiple Agency Theory, Enterprise Ontology, Value Modeling and Speech Acts Theory. We demonstrate our approach on a case scenario based on the Directive 2009/72/EC, which de nes common rules for the liberalization of the European market of energy.

Keywords

• Ontology
• Subjective Values
• Value Networks

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A value network has been initially referred to as a group of enterprises exchanging objects of economic value to satisfy the needs of a market of consumers [13]. Aiming to de ne formally how business actors could collaborate within a value network, Gordijn and Akkermans proposed the e3value framework to support the modeling and pro tability analysis of value networks. The fundamental principle grounding the e3value ontology seems to be the one of "economic reciprocity", which governs how business actors sacri ce objects of economic value to obtain other ones (of equivalent value) in return. There, the di erence between sacri ce and bene t is measured, as objectively as possible, as monetary pro t. It is reasonable that reaching goals stated for this objective value is necessary to the economic sustainability of a value network, but not su cient for a consumer to declare that his business need(s) will be fully satis ed with such a measure of value [ 2, 18 ]. For this case, subjective values such as assurance, privacy and trust might come into play for a consumer not only to di erentiate between equivalent monetary value propositions, but also acquire products and services the valuation of which would depend on previous experience, such as products bought online or innovative services (e.g. smart metering and medical nanotechnology).

Adopting a Design Science perspective on research [19], the research question addressed in this paper is how a value network could be con gured based on subjective values. From an organizational perspective [ 6 ], this question is initially threefold: What subjective values could be considered as important or even essential for consumers in a value network? How to measure these subjective values? How these values might be related to the satisfaction of a certain consumers' business need?

To start addressing these questions from an Information Systems perspective, we propose an ontology for con guration of value networks based on subjective values. The ontology was formalized in Web Ontology Language (OWL-DL), supplemented by a set of rules de ned in Semantic Web Rule Language (SWRL) [11], and blends concepts of the e3value ontology [10], Enterprise Ontology [ 7 ], Speech Acts [15] and Value Monitoring Ontology [ 3 ].

The rest of this paper is organized as follows. In Section 2, we describe a case scenario that motivated our conceptual analysis of the role of subjective values on the con guration of value networks. In Section 3, we describe an ontology for modeling and analysis of what can be named thus far as qualitative value networks. In Section 4, we return to the motivating scenario to demonstrate the modeling utility of the ontology on a case scenario depicted as a value network of Smart Metering services. In Section 5, we provide theoretical conclusions, threats to validity and future steps of this research. 2

Observational Case Study

The case scenario presented in this section is a projection on future markets of liberalized Energy services in Europe, normalized by the Directive 2009/72/EC of the European Union [17], and described in earlier research by Silva et al. [ 2 ]. In this scenario, householders will have the option to choose not only among energy providers, but also smart metering companies that suit their needs the best. As depicted in Fig. 1, the case scenario was shaped as an e3value model. The nal consumer playing the Agency role of a principal is a householder represented by a market segment of Balance Responsible Parties (BRP). EU reports have revealed that one of the main issues on the adoption of smart metering solutions by the European population concerns privacy, that is, energy consumption information might be explored opportunistically [ 1 ]. Hence, householders might consider peer assessment and evaluation of the privacy provided by such an innovative service before entering into an agreement with a metering operator. This is therefore a special business case where it is not only the monetary price of the technology that matters, but also the intangible value to be experienced by the nal consumer.

A BRP is motivated by the opportunity of balancing energy consumption, or even selling unused energy through demand-response of the smart meters. Thus, a BRP has the option to create value from smart metering assets provided as core business objects by a market segment of Metering Operators. A householder might obtain metering accounting or auditing reports from three value paths. In the rst option, the householder could possess a metering asset provided by a Metering Operator, once granted with a Metering Responsible Party (MRP) accreditation by the Transmission System Operator (TSO). In exchange, the householder allows the TSO to have access to private veri able information of energy consumption through an Open (virtual) Monitoring Channel. This is necessary for monitoring and control of the overall state of imbalance reduction of the network by the TSO. In the second option, the householder could delegate the energy metering activity to the peers from which the energy is bought, e.g. aggregators or Distributed Energy Resources (e.g. wind turbine owners), both allowed by law to operate with MRP accreditations. The analysis of qualitative values relevant for the assessment of these options is demonstrated in Section 4.

Semantic Value Network Ontology

The ontology was formalized in OWL and complemented with SWRL rules to allow semi-automatic con guration of qualitative value networks. However, the scope of this paper is limited to the demonstration of the relevance of subjective values on the con guration of a value network.

A business need is owned by a principal consumer (actor or market segment) and is the starting point of con guration of a qualitative value network. A policy may assume ve organizational arrangements (or patterns) that represent di erent con gurations whereby a business need could be satis ed. The conceptual foundation of these patterns is described in detail by Silva et al. [ 2 ] and formalized in OWL in the ontology depicted parsimoniously in Fig. 2. Following the organization of the value network model, the value indicators allow for analysis of the subjective values assigned to products and services o ered as value propositions to the nal consumer. The value indicators not only qualify the economic e ectiveness of a value proposition meeting a business need, but also the economic e ciency of a policy arrangement. Yet, value indicators do not replace the pro tability analysis supported by the e3value framework, but adds an extra layer of information to re ne the selection of value propositions by the consumer. In e3value, the notion of a business need is rei ed as a value object desired by the consumer. Here, this notion is extended by separating the identity of a core business object (i.e. a product or service category) from its value, which can be objective (e.g. quantity, quality, time and location) or subjective (e.g. privacy, reliability or trust). In e3value, a core business object meets a consumer's need when its investment is lower than its sacri ce, which is measured by quantifying the monetary resources paid in exchange for the core product or service provided by the network.

From our best knowledge, objective values such as quality, time and location are not taken into consideration in an e3value pro tability analysis. Despite the importance of these values, we take the e3value quantitative approach as su cient for objective valuation of core business objects and move our discussion into the role of subjective values on classifying value propositions of equivalent objective values. Accordingly, a business need is demanded by a consumer acting as an Agency principal of the network, and is satis ed not only by a core business value object, but also by the value indicator assigned to this object. There are two subclasses of value indicator: objective value and subjective value. Di erent from objective values, subjective values are perceptual, and the assessment of which involves at least two Agency parties and depends on individual experience. The di erence between the perception of two Agency parties on the same value assigned to a value object is a measured value, which has three value partitions: value surplus, value balance and value shortage [16]. The logic underpinning subjective value measurement is detailed further in this section. Moreover, the principal has also a business rationale, e.g. a business weakness, threat or opportunity (the only rationale treated in this paper). A business need is represented as a de ned class in the ontology, as depicted in Fig. 3. A policy is de ned here as an organizational pattern of actors, activities and objects connected by speech acts and inspired by the NIST metamodel of RoleBased Access Control (RBAC) [ 8 ]. Preventive monitoring is intrinsic to Multiple Agency, and the ontology formalizes ve Agency monitoring patterns for value networks, described in detail in Silva et al. [ 2 ]. The patterns are named as single, double-check, chokepoint, committee and gossip, and comprise di erent strategies whereby the principal might evaluate products and services o ered by the network. The pattern described in detail here is the committee pattern, due to its completeness on covering the case scenario. The ontology de nes four actor roles (i.e. principal, third-party, regulator and agent), four value activity roles (i.e. front-end, back-end, resource and regulatory) and four value object roles (i.e. core business, proof-of-performance, certi cation or accreditation and counterobject). Actor roles are connected to activity roles by relationships of authority, competence and responsibility, inspired by the Enterprise Ontology [ 7 ]. Activities roles are connected to object roles by speech acts, (some of them adapted by Enterprise Ontology as production acts) such as produce, consume, grant, transfer, bundle and distribute. The formalization of the committee pattern is depicted in Fig. 4. Subjective values are normally used by consumers when evaluating a product or service before acquisition. Without experience on the use of the product or service, it is also common that consumers consider other peers' evaluation on subjective values of the desired commodity. Such a practice is not recent, and therefore should not be exclusively associated with the current trend of e-Commerce solutions. However, subjective values are shaped not only by individual and private productive acts of experience, but also by social communication, which is closely related to the reputation of a commodity and its respective provider. From a Speech Acts perspective, it is possible to argue that subjective values might assume di erent roles, depending on who is making a (subjective) value proposition to whom.

Taking this perspective into a value network organized with Multiple Agency roles, the nal consumer acting as a principal receives value propositions of core business objects produced by back-end activities of competence of third-parties, and transformed (i.e. bundled, distributed, granted or transferred) into valueadded commodities by agents and regulatory parties. Considering that suppliers acting as third-parties are prone to communicate biased evaluations on their own products or services, it is assumed here that their evaluation on corresponding products or services shall not be fully taken into consideration by a rational consumer. Thence, the social construction of a business value in this case will involve the consumer acting as a principal, agents and regulators.

For the principal, what is relevant is the expectation of value to be created using the product or service produced by third-parties. In this sense, the principal initially predicts his expected value for the commodity to be acquired. Nonetheless, for the agent and regulators, whose evaluation will be considered by the principal on acquiring the commodity, and who somehow experienced or sensed the value of the commodity, the subjective value will have the role of perceived value. While a regulator testi es his perceived value of the commodity by verication or witnessing, an agent reports own perception on the same commodity through business transformation. The description logics de nition for subjective value and corresponding value scales (or partitions) are depicted in Fig. 5-a and Fig. 5-b, respectively. The SWRL rules for assignment of expected and perceived values are summarized in Table 1.

Value perceived by ssvvnn::Stuebsjteicftiievse/Vraelpuoer(t?ss()?^p,?svp)^

the agent svn:SubjectiveValuePartition(?svp) ! svn:hasPerceivedValue(?s, ?svp)

Value perceived by ssvvnn::Stuebsjteicftiievse/Vraelpuoer(t?ss()?^p, ?svp)^

the Regulator svn:SubjectiveValuePartition(?svp) ! svn:hasPerceivedValue(?s, ?svp) svn:Regulator(?p)^svn:hasSubjectiveValue(?p,?s) ^

Subjective value is a class de ned as an enumerated set of partitions adapted from the SERVQUAL model to express measures for expected value or perceived value, as depicted in Fig. 5-b. Accordingly, the value partitions comprise: ideal value, forecasted value, equitable value, deserved value and minimum tolerable value [14]. The di erence between expected value (predicted by the principal) and perceived value (testi ed by at least one regulator and reported by at least one agent) is assessed qualitatively as measured value. The logic underpinning the qualitative assessment is formalized in SWRL rules summarized in Table 2.

Demonstration: A Case Scenario in Smart Metering

We now return to the case scenario introduced in Section 2. The problem of this case is how a householder could analyze value propositions of smart metering services based on qualitative values that this technology might return. Earlier research conducted by the European Commission has uncovered privacy as a key value expected by the European population to be o ered by smart metering operators. As smart metering assets are becoming more intelligent and innovative, the acceptance of this technology by European householders shall depend, among many other factors not covered in this paper, on progressive peer evaluation of subjective values such as privacy to be created using this technology. This evaluation can be supported by e-Government channels providing transparent accounting of infrastructure services to the population [ 4 ].

Hence, to decide which metering operator to choose, a householder might take into consideration some evaluation provided by agents that used the technology. After declaring a business need of a smart metering service and predicting a subjective value to be created by its use, a householder has the option to select one among many policies whereby the desired commodity could be acquired. The Agency monitoring patterns proposed by Silva et al. [ 2 ] can be used for this purpose. For brevity, our demonstration will be resumed to the committee pattern.

Once the policy pattern is selected, the next step is to evaluate its internal subjective value propositions for the smart metering asset as a core business object. In this case scenario, the BRP's business need could be satis ed by the metering asset prospected to o er the best level of privacy, as a subjective value of relevance. This prospection has been referred in this paper as measured value, which is de ned by the di erence between the principal's expected value of the core business object and the agents perceived value of the same object, based on previous experience or use. Let it be supposed that: (1) the market segment of Metering Operators acting as third-parties has three individuals for analysis; (2) the BRP predicts an expected value for the metering asset as equitable; (3) the MRP-Aggregator reports a perceived value as forecasted ; and (4) some MRP-DER reports a perceived value as equitable;

Then, the rules for de nition of the measured value taking the BRP's perspective as dominant apply as summarized in Table 3. Accordingly, it is possible to notice that the metering asset provided by the Metering Operator 1 is prospected to generate value surplus as a measured value on the BRP's side. svn:hasSubjectiveValue svn:hasSubjectiveValue (svn:BRP, svn:Privacy)^ (svn:BRP, svn:Privacy)^ svn:hasExpectedValue svn:hasExpectedValue (svn:Privacy, (svn:Privacy, Metering svn:EquitableValue)^ svn:EquitableValue)^ Operator svn:hasPerceivedValue svn:hasPerceivedValue 1 (svn:Privacy, (svn:Privacy, svn:ForecastedValue) svn:IdealValue) ! svn:hasMeasuredValue ! svn:hasMeasuredValue (svn:SmartMetering, (svn:SmartMetering, svn:Surplus) svn:Surplus)

5 Conclusions and Future Research

In this paper, we have addressed the research question of how a value network could be con gured based on subjective values. We recognize that meeting a consumers' need with value objects exchanged by a reciprocate monetary price is necessary, but insu cient to state that the need will be ful lled. The ontology proposed here de nes a business need as a composition of a desired value object (i.e. a product or service category) and its value components (i.e. objective or subjective values). For objective value assessment, we recommend the use of the e3value mechanism of pro tability analysis to verify the objective values of quantity and quality (e.g. monetary price) assigned to value propositions. For subjective value assessment, we assume that values such as privacy, security and trust are perceptual and dependent on social communication. Accordingly, the ontology includes ve Agency monitoring patterns of Silva et al. [ 2 ] to indicate the provenance of the value propositions that will possibly satisfy a consumer's business need. For simplicity, only one pattern is demonstrated in this paper. Moreover, the ontology is complemented by a set of SWRL rules to support semi-automated classi cation and selection of value propositions based on the need of value surplus on the consumer's side.

Gomez-Perez [ 9 ] proposes a framework for ontology evaluation, which comprises three phases: (1) veri cation of correctness, consistency and completeness; (2) validation via theoretical demonstration, prototyping or case study application; and (3) evaluation of community acceptance, modeling utility and usability. The correctness and consistency of the ontology has been checked by using OWL2 and a SRWL plugin for Protege [12]. Completeness has been veri ed according to an Ontology Requirements Speci cation Document (ORSD) not described in this paper. For validation, we have been using observational case studies in digital music clearance [10], energy imbalance reduction [ 3 ], and customs control [ 5 ] for research problem exploration and technology evaluation. Thus far, the ontology has not yet been applied in interventional case studies or submitted to users' evaluation and surveying, which comprise the current threats to validity of this research.

For future work, this research will follow three directions. First, a more precise characterization of subjective business values demands philosophical grounding. Business values should not be misinterpreted as soft goals (as de ned in Requirements Engineering) or Non-Functional Requirements (NFR) analysis. It is necessary to investigate the role of subjective value analysis for the overall sustainability of value networks. Second, it is necessary to design a mechanism for integrity check of transactions that compose a value network, also taking subjective values into consideration. For a while, our analysis is driven by a Service Dominant Logic, focused on a single consumer's business need. However, it is relevant to resolve two or more business needs covered by a same value network. Third, the logic of qualitative assessment proposed here will be revisited based on related research in gossip algorithms and evaluation of products and services provided by e-Commerce platforms. 10. Gordijn, J., Akkermans, J.: Value-based requirements engineering: exploring innovative e-commerce ideas. Requirements engineering 8(2), 114{134 (2003) 11. Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al.: Swrl: A semantic web rule language combining owl and ruleml. W3C Member submission 21, 79 (2004) 12. Musen, M.A.: The protege project: a look back and a look forward. AI matters 1(4), 4{12 (2015) 13. Normann, R., Ramirez, R.: From value chain to value constellation: Designing interactive strategy. Harvard business review 71(4), 65{77 (1993) 14. Parasuraman, A., Zeithaml, V.A., Berry, L.L.: Servqual: A multiple-item scale for measuring consumer perc. Journal of retailing 64(1), 12 (1988) 15. Searle, J.R., Vanderveken, D.: Foundations of illocutionary logic. CUP Archive (1985) 16. Steedman, I.: Positive pro ts with negative surplus value. The Economic Journal 85(337), 114{123 (1975) 17. Union, E.: Directive 2009/72/ec of the european parliament and of the council of 13 july 2009 concerning common rules for the internal market in electricity and repealing directive 2003/54/ec. O . J. Eur. Union L 211, 55{93 (2009) 18. Weigand, H., Johannesson, P., Andersson, B., Bergholtz, M., Edirisuriya, A., Ilayperuma, T.: Strategic analysis using value modeling{the c3-value approach. In: System Sciences, 2007. HICSS 2007. 40th Annual Hawaii International Conference on. pp. 175c{175c. IEEE (2007) 19. Wieringa, R.J.: Design Science Methodology for Information Systems and Software Engineering. Springer, Heidelberg (2014)

References

1. European commission: Country ches for electricity smart metering (accompanying the document), report from the commission, benchmarking smart metering deployment in the eu-27 with a focus on elec-tricity . swd ( 2014 ) 188 nal , brussels, 17 june ( 2014 )

2. de Alencar Silva , P. , Bukhsh , F.A. , da Silva Reis, J., de Castro , A.F. : Agency monitoring patterns for value networks . In: International Conference on the Economics of Grids, Clouds, Systems, and Services . pp. 81 { 93 . Springer ( 2017 )

3. de Alencar Silva , P. , Weigand , H.: Enterprise monitoring ontology . Conceptual Modeling{ER 2011 pp. 132 { 146 ( 2011 )

4. Bertot , J. , Estevez , E. , Janowski , T. : Universal and contextualized public services: Digital public service innovation framework ( 2016 )

5. Bukhsh , F.A. , Weigand , H.: Smart auditing{innovating compliance checking in customs control . In: Business Informatics (CBI) , 2013 IEEE 15th Conference on . pp. 131 { 138 . IEEE ( 2013 )

6. Cameron , K. : Critical questions in assessing organizational e ectiveness . Organizational dynamics 9(2) , 66 { 80 ( 1980 )

7. Dietz , J.L. : Enterprise ontology: theory and methodology . Springer Science & Business Media ( 2006 )

8. Ferraiolo , D.F. , Sandhu , R. , Gavrila , S. , Kuhn , D.R. , Chandramouli , R.: Proposed nist standard for role-based access control . ACM Transactions on Information and System Security (TISSEC) 4 ( 3 ), 224 { 274 ( 2001 )

9. Gomez-Perez , A. : Ontology evaluation . In: Handbook on ontologies, pp. 251 { 273 . Springer ( 2004 )