Human Centricity as Leading Design Principle for Smart City Innovations: Implications for the Governance, Control, Reporting and Performance Evaluation of Well-being of Civil Society Actors

After reviewing the clauses in Directive 2013/34/EU, 2014/95/EU, and 2013/50/EU, the Commission asserted that there is significant evidence that many undertakings like businesses do not disclose material information on all major sustainability topics including climate related information, such as GHG emissions and factors that affect bio diversity. Two major problems were recognized: (1) The reported information is limited comparable and (2) the reliability of the sustainability information is to be debated. These issues among others motivated CSDR-2022 providing in the need of a robust reporting framework, that is accompanied by effective auditing practices to ensure the reliability of data, avoid green-washing, and double counting.

The nature of the data businesses have to report is two fold. On one hand, we have the reporting information to the extent necessary to understand the development of the business and the performance of the enterprise. On the other hand, companies need to report about the impact of the undertaking its activities on environmental, social, employee matters and on how sustainability affects the company. This is what is to be understood as the double materiality perspective. In general, impacts concern three types of impacts as we put it. First, we have impacts directly caused by the company. Secondly, there are impacts to which the undertaking contributes. Thirdly, we have impacts which are otherwise linked to the undertaking’s value chain. Additionally, the CSRD-2022 stipulates that sustainability information should take into account short-, mid-, and long-term time horizons and that the information must address the whole value chain of the company including its own operations, products and services, business relationships, and supply chain.

So reliability of data concerns both (impact) perspectives and is closely related to the undertakings business model and the chosen revenue models which determine the net revenues of an enterprise and the associated costs to deliver the goods and services to the customer of the undertaking coined as civil society actor. From a governance perspective, the two identified user groups want to learn, i.e., want to be informed about the strategies the business undertakes to cope with the impacts, and they want to know how well the performance of the business actually is in dealing with sustainability related governance and control risks. Think of the following: (1) Elimination, no longer perform the risky activities, for example by refocusing the strategy or alter policies, (2) centralization, restrict decision rights to senior management or governmental decision-making units, (3) risk-sharing, sharing risks with other stakeholders, for instance by taking out an insurance or by pooling resources together, (4) automation, reducing the opportunities for violations by automating service processes, and (5) the choice for behavioral controls, reducing the risks by taking either preventative control measures, which will make the risk impossible or unlikely, or by taking detective and corrective measures, which will make the impact of the risk less severe [14].

NIST defines measurement as an experimental or computational process that by comparing with a standard as a norm, produces an estimate of the true value of a property of a material, a (virtual) object, a collective of (virtual) objects, a process, an event, a series of events, together with an evaluation of the uncertainty associated with that estimate and intended use in the support of decision-making. Measurement uncertainty concerns, i.e., expresses the doubt about the true value of the measurand as the estimate of the true value of a property as defined after a measurement. The doubt relates to or is associated with the level of rigor to be determined on the level of uncertainty and what is needed to demonstrate its credibility which determines the adequacy to meet users needs and wants. Most probably, the adequacy is influenced by regulatory rules and regulations set by governmental bodies like governments, customers, demand, reputation of the company, ethical standards, and so on. This makes traceable to standards and assurance a complex endeavor to reach and maintain traceable performance standards.

Traceable to (SI) standards is not the same as counting objects. A claim that counts, as a result of a sample, are traceable to (SI) standards is not correct because it neglects the fact that counting inextricably involves the definition of what is being counted which definition is not a part of the (SI) standard, but when some characteristic of the object is measured then it might be possible that this particular measurement result is traceable to the (SI) standard. Making counting traceable to the (SI) standard is very important for economic live, one’s health, one’s security, and so on. The value lies in the precision of the measurement and therefore the measurement result. Put in other words: “Knowing the measurement uncertainty contributes to one’s belief whether a measurement result as a count represents the quantity one has measured traced back to the (SI) standard”.

This is very important to be aware that measurement uncertainty is about the doubt related to or is associated with the level of rigor to be determined on the level of uncertainty and what is needed to demonstrate its credibility which determines the adequacy to meet users needs and wants. In the case of sustainability reporting a very important notion, we give the following example.

Now we see that the Brix scale is quite informative for customers from a health perspective and that there is a causal linkage between buying and selling tomatoes.

In [9, 11, 12], we introduced the canonical model of exchange relationships market view and the extension to the organizational view on exchanges between two or more agents like buyers, producers and sellers. Exchanges are by definition reciprocal in nature and come in a large variety of what we coin as means like signed contracts, shaking hands, and so on. For example, signing a contract by both parties is performative in nature; by the act of signing, we communicate that the exchange is done. Hence a signed contract affords exchanging. An affordance establishes the relationship between an object or an environment and an organism here a (human) agent through a stimulus to perform an action. In our example, the stimulus is the signed contract and the detectable change in the external environment. We assume that the agent is sensitive and therefore able to respond to external (or internal) stimuli. Bilateral contracts are commonly used in business transactions. You buying two kilograms of tomatoes in our example is a type of a bilateral contract. The grocer promises to deliver the tomatoes where you promise to pay for the tomatoes by giving the grocer the indebted amount you have agreed upon when receiving the tomatoes. More formally we can depict the canonical description of a value exchange cycle as in Figure 4. We use the following notation.

Note that money is exchanged for goods and or services. The exchange will actually occur in practice when parties agree upon a contract, i.e., the transaction governance, the transaction structure and the transaction contents, by the act of signing denoted by the initial node depicted as a solid circle. The contents reflect the objects of exchange. In our case, tomatoes. Now it is possible to extend the bilateral contract from a market point of view, as depicted in Figure 4, into a value exchange cycle from an organizational point of view. The final result is depicted in Figure 5.

This concludes our canonical (informal) description of bilateral contracts used in value exchange situations. We have shown in [11, 12] that under specific conditions, the market view model is equivalent to the organizational view model. It is also easy to see that the organizational point of view is easily extended into a net(work) of contracts similar to supply chain models commonly used in logistics [24, 40]. In Section 8, we will elaborate on the notion of networks in regard to sustainability informational needs.

In a bilateral exchange relationship, money is exchanged for goods and or services. This is true from the buyers’ perspective as well as from the sellers’ point of view. We say that the proportion goods and or services to money equals the proportion of money to the goods and or services. So we get the following equality:

Let \(\chi\) denote the goods and \(\mu\) denote the money, so we get:

Nodes S and B are in fact rationals, defined as follows [38]:

Given the definition of a rational remark that money, goods, and services are not equal objects, but that the exchange relationship itself is equal. We observe thatand

It follows that the following equality holds:

To be precise, the bilateral exchange relationship preserves the identity of the objects denoted as rationals. Consequently, S delivers \(\chi\) , denoted as \(S \cdot \mu\) and B pays the money \(\mu\) , denoted as \(B \cdot \chi\) . Mark that \(\iota\) denoted as a loop in the graph serves as an explicit precondition(s). Now we can label the nodes and edges.

Remark that up till now our notions of goods, services, and money are in fact dimensionless. Parties will also have agreed upon the unit of measurement of the goods or services the seller will deliver and get paid for, respectively, the buyer will receive and is obliged to pay for the received goods or services from the seller. We will use the following notation.

We denoted \(\chi\) for the goods and services and \(\mu\) for money. For the sell side, we get:

For the buy side, we get:

As we have noticed earlier, trace-ability to (SI) standards is not the same as counting objects. A claim that counts are traceable to (SI) standards is not correct in the case one neglects the fact that counting inextricably involves the definition of what is being counted which definition is not a part of the (SI) standard. The canonical model of the bilateral contract ensures that all characteristics of an object can be identified and thus be measured so that the particular measurement results are by design traceable to the (SI) standards.

Remark that money is considered as an abstract object like goods and services. As we will see later, it is this particular characteristic which is very convenient, i.e., helpful, but first we have to extend our model to fit the organizational view. To do so, we have to extend our definition for rational numbers for sum, product, negation, subtraction, and quotient:

Additionally, we introduce the notion of distance as a concept to understand the difference between what an undertaking buys and what an undertaking sells in the market.

It follows that d(x,y) = 0 if and only if x = y and d(x,y) \(\ne\) 0 if and only if x \(\ne\) y.

Translation of the value cycle exchange market view of the bilateral contract into a directed graph representing the bilateral contract organizational view we get the following result:

Subtraction of rationals is defined in Equation (14). When we apply subtraction of B and S’ and take the absolute value, then we get the distance:

Extending the graph gives us the following result:

When we interpret the graph, then it is easy to see that \(\delta\) is only meaningful if and only if the units op measurement are identical. The following axioms must hold:

In the case B and S’ are the same agents as S and B’, then \(\delta\) = 0. In the case they are not the same, agents then \(\delta\) can have three values of which exactly one of the three statements x = y, x < y, or x > y is true. It follows that when x = y then the following laws hold:

If x < y or x > y is true, then the following equalties hold, respectively:

Remark that we are interested in the proportionality and not in the quotient arithmetically, although this can be very helpful as we will see.

With this description, we have a formal account of what is to be understood as preservation laws in accounting systems buttressing the core attributes consistency, predictability and neutrality ensuring the information quality as measurement. In the auditing, accounting and control literature known as reconciliation controls. The equalities (23) and (24) buttress the commonly known accounting equations which is the basis for what is known as double entry booking practices.

In Section 6.1, we described the formal preservation laws which ensure that the information is consistent and predictable. The notion units of measurement gives the strict definitions of the object being measured so that neutrality is “guaranteed”. But how does this logic, i.e., model, relate to (accounting) information systems. Indeed how does the bilateral contract - organizational view relate to databases which is the founding mechanism for reporting, performance measurement and performance evaluation. For this, we use a process language based on unified modeling language (UML).

For our purposes, it suffices to use UML because UML provides in a common meta-model that formally defines the abstract syntax of all sorts of diagrams for modeling process behavior. The declarative meta-model is a very good alternative to grammars used to define formal languages. In our exposition, we use activity diagrams to model process behavior. The next section is based on [18].

Actions describe the tasks that have to be performed in realizing a primary function to be viable [1]. An action stands for some transformation in the modeled system to be performed. The sequence in which the actions must be executed is the most fundamental control structure. As we have seen actions in our language are denoted as round-edged rectangles. The arrows between the action nodes are the activity edges which specify the control flow. Together with the initial and the final node depicted as a solid circle and a solid circle surrounded with a hollow circle, we have a correct specification of the control flow (see Figure 6).

The semantics is defined as a token flow which can also be used to refer to data and physical objects. The tokens are referred to as control tokens, respectively, as object tokens. Mind that actions can only start when tokens are available from the proceeding action or actions along the incoming edges. We say that tokens are consumed when an action starts. Consequently, tokens are produced, i.e., offered, to the outgoing edges when completed. In some circumstances decisions have to be made for the choice of alternative control flows. Decision nodes are denoted as diamonds annotated by guards. The extended control flow can be depicted as in Figure 7. Guards are logical expressions ending up to be true or false. Either we can state them in natural language, programming language constructs or in formal mathematical logic. Guards can be refined as being pre- and post conditions. When needed we will introduce them. The control logic remains the same. There are many more types of nodes used in modeling control flows such as fork nodes, merge nodes, and join nodes. These type of nodes can be useful.

Finally, we have two types of nodes which are essential for our purposes. These are object nodes and data store nodes. Object nodes are needed to model the occurrence of objects at a particular moment or point in the process. Objects can be typed. We will extend this formalism extensively for our theory. To capture the object flow, the token flow semantics of activity diagrams is extended with object tokens. An object token behaves like a control token but it carries additionally a reference to a certain object type. Remark that we have to consider object type compatibility. A very convenient modeling notion is to use input pins and output pins which enables us to know which input and output parameters are assigned to various actions in the process. Pins are depicted as small hollow squares with their type written next to the square. In the case we want to store information about orders, for example, then we can model such an action as a data store using data store nodes denoted as a rectangle. A data store node keeps all tokens that enter it, copying them when they are chosen to move downward. See Figure 8 for an example.

Now we can extend out bilateral contract - Organizational view to get a clear view about the informational needs and therewith next to it the requirements to meet a company’s control and auditing objectives. The result is depicted in Figure 9.

Our objective is to assert whether the data stores as depicted in Figure 9 can be considered to be accurate. More specifically, these data stores enable us to extract one or more data files we need as input data in our decision, i.e., evaluation procedure to assert the accuracy of the extracted dataset(s) and its acceptability, i.e., adequacy for quality control, quality audit purposes, and performance evaluation. In our example, we have identified data about stored goods, data about order picked goods (to be) delivered, data about the collected revenues of the goods sold, and data about the actual payments of invoices received from suppliers for the goods we have received and stored in the warehouse.

In Section 4, we elaborated on the concept of data integrity. In Figure 3, we depicted the accuracy data model and its key aspects which determine the accuracy of the data. There are three major aspects which determine the accuracy of the data and therefore its data integrity. These are as follows:

All other aspects are derived notions necessary to trust the data and to strengthen one’s belief that the information integrity is assured. Consistency has a variety of meanings like coherent, consistent, cohesive, connected, connective, sequacious, and so on. So it is important to be specific about what is to be understood in the context of data accuracy. As we can see, there is a strong relationship between the contract with the supplier and the purchase order of the goods or services. The contract specifies the conditions the organization and the supplier agreed upon. So we have data about the price, quantity ordered, and the quality norms applicable to the goods and or services. The same is true for the contract agreed upon with the customer and the sales order. Remark that next there is a strong relationship between ordering goods and money outflow due to paying the invoice. The same is true with respect to the sales of the goods and services and receiving the money. The type of controls to re-perform the relations are called reconciliation controls which type directly follows Section 6.1 —extended graph bilateral contract—Organizational view and Figure 9 control flow extended.

Consider the control flow as depicted in Figure 9 in more detail. On the left, we recognize the bilateral exchange relationship coined as a buying contract from the perspective of the enterprise. On the right-hand side, we see the bilateral exchange relationship coined as a sell contract. The nature of signed contracts can be cast in terms of generalized notion of promises, i.e., autonomously given declarations of expected behavior which stem from some identifiable characteristics. Promises are related to intentions and are both closely related to the idea of preferred outcomes. In short, an intuition is the selection of a possible outcome, based on optimization of some criteria of success. To do this efficiently we label noisy data to a simple(r) symbolic discriminant. Promises are labels that align with intended outcomes and offer a framework for reducing uncertainty about the outcome of certain events, i.e., actions [8].

When we consider a buying contract, then there is an expectation that the supplier will deliver the goods and that the supplier has the expectation that the buyer will pay for the goods. This brings us to the following intuitive definition:

There are some number of assumptions:

Accounting information systems are by design labeling systems known as accounts. In the case the buying contract is signed by both parties involved there is an expectation that goods will be delivered, at some moment in time, in some quality, in some quantity with a value in total due to the supplier. These types of data will be registered in the accounting information system with a meaningful label, i.e., account description like goods on the way. Simultaneously, the value due to the supplier, i.e., the promised payment will also be registered with the meaningful label like invoices supplier on the go. Similarly when the goods are received then the following data entry will be made with a label like goods received. Simultaneously, the account with label goods on the way is updated for the same information goods received was updated. All these events / actions make up a trace in the accounting information system, when summarized this gives us the money and good flow of an undertaking over a period. Ultimately, this gives us the balance sheet per some date and the profit and loss account over a period of time. In the next section, we will give the precise treatment on how the mechanism works.

Referring to the notion of data quality as discussed in Section 4 and the information flow about measures, goods, and money flow as depicted in Table 4, we are able to formulated the decision procedure as an assessment procedure to make an assessment about the accuracy of the data stored in an accounting information system. The accuracy of a data store under consideration is said to accurate when the following proposition holds:

The result can be depicted as a tree. On top, we have the data stored in an accounting information system. On the left, we have the output after checking whether the syntax is correct. The \(\bot\) denotes the attributes which are false. There are two possibilities either the syntax of type is wrong or the attribute is empty. On the right hand, we have the output whether the timelines is correct or not from a completeness or validity perspective.

This gives us the information from an assurance perspective whether the internal controls are effective. In general, internal controls defined as processing and accounting controls preserve the data integrity. The output of the assessment procedure coined as assurance gives us the information about the accuracy of the data itself upon which we have to build reporting systems encapsulating financial and non-financial information. Conceptually they share the same objects, so the outcome of our assessments gives us the information depicted as a tree.

We refer to [12] for further details and the underlying theory and practice within a quality control and audit perspective.

Answering and discussing the capitals we have to report upon implies the key challenge an undertaking faces to create a shared vision among stakeholders and thus shared mental models that guide local decision makers constituting an ecosystem making up a value chain intended to create business, social, and environmental value. A shared vision is similar to what is coined as belief and boundary systems [34, 35]. Belief systems can be thought of as the core values of an organization where boundary systems stake out the strategic territory related to business activities that are strictly ethically prohibited. No need the stress the fact that boundary and belief systems are closely linked. A vision contains, i.e., envisions, the outcome of the deliberation process discussing the desired outcomes in a coherent, consistent, and sequacious way. Envisioning and deliberating can be thought of an interactive control system which mechanism buttresses the dialogue among stakeholders [6] to manage strategic risks an undertaking has to cope with. In this dialogue stakeholders need diagnostic control systems to monitor the actual performance of the business system behavior. This information needs to be useful and relevant [7, 28].

The design question buttressing the reporting system is diagnostic in nature and the reasoning style is abductive. Traditional the diagnostic problem is framed in situations where an observation of the system’s behavior is functioning abnormal or even fails to function at all. The issue is then to determine those components, objects, and so on of the system that will explain the difference between observed behavior and the desired correct behavior [31]. To solve the aforementioned diagnostic problem from first principles, only the information of the system description is available together with the observation of the actual behavior. Building on the work of [25] Reiter provides in a theoretical foundation for diagnosis from first principles. As he observed and demonstrated many different logics lead to the same theory of diagnosis. In our situation, there is one major problem and that is we cannot observe actual system behavior just because the system has to be designed yet. We do have a shared expectation about the expected behavior and we aim that the accounting system after being build and implemented shows in practice the shared expected behavior. Indeed we have to consider that there is a possibility that the actual behavior after having the system built and implemented can actually differ from the expected outcome and we will need safeguards upfront to be considered in designing the system. In [9], we coined this requirement incentive-compatible (direct or encoded) revelation mechanisms. It needs no elaboration that the design question and the diagnostic problems both sh@ARTICLE 9963762, author = L. G. Anthopoulos and M. Janssen, journal = Computer, title = Business Model Canvas for Big and Open Linked Data in Smart and Circular Cities: Findings From Europe, year = 2022, volume = 55, number = 12, issn = 1558–0814, pages = 119–133, abstract = This article introduces a business model for big and open linked data in smart and circular cities, laying the foundation of a new approach that generates societal, business, and public value., keywords = linked data;computational modeling;urban areas;europe;data models;business, doi = 10.1109/MC.2022.3194634, publisher = IEEE Computer Society, address = Los Alamitos, CA, USA, month = dec are the same mechanisms and principles. The diagnostic cycle can be depicted as in Figure 10 [25].

The main objective is to design a system that minimizes the expected structural discrepancy between the model and the artifact realizing the goal function. For example, if the sustainability goals are the result of an ongoing dialogue with stakeholders than a model based on the axioms of such a belief defined as a promise, decided to be foundational and strictly normative in the deontological sense, then the accounting and reporting system as an artifact is to be designed to monitor the behavioral discrepancies between predicted agreed upon normative behavior and the observed normative behavior. Needless to say that strict rules should be enforced upon the agents who are responsible as accountable on merit grounds. Indeed the verification procedure applied by the undertaking communicates the outcome of the verification procedure by means of a reporting system. Differences should be recognized and the undertaking has to inform the agent(s) and stakeholders whose action is not compliant to the applicable rule so corrective action must be taken or is to be punished by some rule.

Senior management and stakeholders must be informed about the effectiveness of these measures making up the internal control system. But we cannot rule out that an autonomous agent, i.e., senior management and stakeholders do not agree to the full extend about what has been decided. In this latter case, we cannot rule out by design any possible behavioral discrepancy of an agent or stakeholder. In general, there are two options for the parties involved. The first option is to take another close(r) look at the actual axioms, presumptions buttressing the accounting and reporting model as in our example we started with in the first place. The second option is to introduce more rules and enforce harder. The designers have to make a choice: “Which path to follow?” If it is possible to reconsider the earlier made choices than the revision process will be commenced. Whether this type of rule is accepted is a fundamental design question addressing moral agency and ethics subsumed in the integrity climate of an undertaking and the integrity of the stakeholders. So the design question is lesser a technical question but merely a social construct.