Data Collection
Sociometric data were collected on all cases of corruption occurring in Indonesian local governments published in The Jakarta Post in the period 2001–2013. The number of cases was 190. The newspaper reports provide detailed information on the structure of corruption networks (e.g., type of actor, type of relations, and type of corruption). Many are based on publicly available court files.
Since the actual incidence of corruption is unknown and these cases are all instances of detected corruption, this sample cannot be used to produce a fully representative picture of corruption networks in Indonesia. However, it offers the opportunity to explore variability in the social-structural foundations of these particular corruption cases in the two phases of decentralization.
The Jakarta Post is a leading online English-language newspaper published daily in Indonesia. It also covers corruption cases at the regional level. A case reported in The Jakarta Post has some importance, and thus it is highly likely that other newspapers will cover it. To start sampling from local newspapers would have created two problems: first, their quality is not always assured and second, the opportunity to cross-check with other newspapers would have been lower, since not all cases may make it into the media outside the local setting (because a case might be considered ‘minor’). To minimize data selection bias and ensure the consistency of the reported information, the reported cases in The Jakarta Post were cross-checked with information from other reliable national and local newspapers that belong to the same and different media groups with The Jakarta Post.
The newspaper data were also cross-checked with report documents from the General Attorney Office and Corruption Eradication Commission. Compared to the court verdict reports, the newspaper reports sometimes gave more details related to the actors’ network and the transaction processes, salient information for reconstructing the corruption network in this study.
Two time periods for comparison were used: corruption cases in the first phase (2001–2004) and in the second phase of decentralization (2005–2013). To reduce potential selection bias between two phases, we included all reported corruption cases from both periods.
- Figure 1 about here -
Newspaper data collection was completed in three stages (see Figure 1). We first identified and collected articles related to corruption cases at local levels as reported in The Jakarta Post. We recorded the individuals (e.g., a mayor) or groups of individuals (e.g., local council) involved in corrupt transactions. We apply a broad definition of public corruption, including bribery, embezzlement, bid rigging, fraud, kickback, graft, favoritism, nepotism, and money laundering.
The search produced 540 articles. In a second step, we reviewed the content of articles, removed articles that merely repeated news and listed the articles in order of corruption case, so that we could calculate the total number of corruption cases covered in The Jakarta Post in the selected years. This check identified 34 articles with repetitive information, which were removed from the collection, resulting in a total of 506 articles, covering a total of 190 corruption cases. Of the 190 corruption cases in our dataset, 96 cases occurred in the first phase (2001–2004) and 94 cases in the second phase of decentralization (2005–2013). In a third step, cross-checks of reported information from The Jakarta Post with other newspapers resulted in the inclusion of 398 related articles. In total, the search yielded 904 articles.
Measurement
Three levels of analysis are distinguished: actor, dyad (i.e., pair of actors), and the corruption case or network. Actors can belong to multiple dyads. For a case in which n actors are involved, there are n(n−1)/2 dyads, and each actor is involved in n−1 dyads.
Based on four types of relations mentioned below, a network of corruption was constructed for all 190 cases. For each corruption case and each type of relation, we derived a binary sociometric containing information about the tie between each individual sender and receiver in the network, with a value of ‘1’ indicating a tie originating from the sender (row) to the receiver (column), and ‘0’ indicating the absence of a tie. The diagonal of each matrix (which would have referred to self-ties) was coded as 0 without any intended meaning.
A tie was coded as a profit relationship if the texts indicated some transfer of benefits (material payment, information, rights, protection, project, and support) from a sender to a receiver. Since unreciprocated transfers were possible, ties could be either symmetric or asymmetric.
A tie was coded as an authority relation if two individuals in the bureaucracy were connected through a formal power relation. This relationship is asymmetric by definition, with the cell entry “1” indicating “sender is superior of receiver”.
Work relations were coded if two individuals are peers in a bureaucratic hierarchy (e.g., both members of the same department). This relationship is symmetric by definition. Authority and work relations are both situated in an organizational setting (in this case, government bureaucracy).
The final category groups individuals connected through either a kin- or a friendship relation, which also were coded as symmetric.
The combination of these four relations constitutes a multivariate network (Wasserman & Faust, 1994) where the relations are profit, authority, work, and kin/friend, of which by definition the last two are symmetric and authority cannot be mutual; further, authority and work are mutually exclusive relations. The data set was analyzed with R (R Core Team, 2022) scripts written specifically for this study.
Actor and Dyad-Level Descriptives
The 190 cases have a total of 1,960 actors. There are 33 cases of only two actors, 35 with three, 29 with four actors, and then it starts to taper off; the three largest cases have 48, 76, and 100 actors, respectively.
The total number of dyads is 28,725. The type of a dyad, considered as an ordered pair, is the combined configuration of the four types of relations: non-embedded corruption (in, out, or mutual), authority (null, in, or out), colleague (null or mutual), and kin/friend (null or mutual).
When considering the unordered dyads there are 20 logically possible configurations[1], of which 14 actually occurred, and seven in more than 0.1% of the dyads. There were 11,827 dyads with a transfer of profit. There were three dyad types occurring in only one case, in each of which kinship/friendship co-occurred with work or with authority. To prevent an overly complicated classification, these co-occurrences were grouped under the kin/friendship category. This leaves seven dyad types with profit transfer: (1) non-embedded bilateral profit; unilateral profit with (2) work, (3) kin/friend, and (4) authority; and bilateral profit with (5) work, (6) kin/friend, and (7) authority.
Table 3 provides the dyad count of these seven dyad types and the proportion of cases in which any of these dyad types is present. This represents aggregates of the multivariate dyad census, after the grouping mentioned above, for dyads with unilateral or bilateral profit transfer. The total dyad count is dominated by the networks with large numbers of actors; therefore, the proportions of cases including a given dyad type were added. From this table the following conclusions can be drawn. It is noteworthy that unilateral profit never goes in the direction opposite to authority; not surprising, but a confirmation of the power of authority in a bureaucracy. The dyad type with the largest number, 10,1490, is for work relations with bilateral profit; this large number is dominated by contributions from nine cases with each more than 100 dyads of this type, all in the first phase. However, the dyad types occurring in the largest proportions of cases are unilateral transfers of profit in an authority relation (0.637) and non-embedded bilateral profit relations (0.484). Bilateral profit exchange dyads occur in 75.4% of the cases and dyads with unilateral profit transfer occur in 67.4% of the cases. Most cases (68.4%) contains dyads in the context of an authority relation.
- Table 3 about here -
Analytical Strategy
The main purpose of the analysis in this paper is to examine the differences between the first and the second phase of decentralization from the viewpoint of the two theoretical propositions presented above. The compoundness proposition stated that in the second phase there will be a higher proportion of compound role structures, i.e., role structures where of the three embedded types (work, kin- and friendship, authority), more than one is present. The intermediary proposition was that the second phase will see a higher proportion of role structures with closed third-party intermediaries (advisors or closed facilitator structures).
For a comparison between the two phases, the analysis has to move from the dyad level to the network level, which is equivalent to the case level. To bring some order in the multitude of these multivariate networks, we construct a classification of the networks depending on the embeddedness in work, authority, and kin/friend relations, and the presence of third parties. We first define the role structure of the network as the set of profit-related dyad types occurring in the network. In other words, we focus on the seven dyad types with profit transfer mentioned above, and categorize the cases according to which of these seven occur in the given case. The number of theoretically possible role structures is the number of non-empty subsets of the set of seven dyad types, which is 27‒1=127. We reduce this further according to the presence of the four types of relation (work, authority, kin/friend, and profit), as indicated in Table 4.
Second, we consider the presence of third parties by distinguishing between networks consisting of only two actors (no third party) and those consisting of three or more (third parties present; grouping together the three different third party types: guarantor, advisor, facilitator). The twelve groups of role structures can be combined with the presence of third parties; it is evident that for the role structures defined in Table 4 by “some dyads …, others …”, third parties are present by definition.
- Table 4 about here -
Non-compound and compound role structures need to be distinguished. The first set of six role structures (rows 1-6) in Table 4 are non-compound, representing ‘pure’ (or uniplex) profit, or profit combined in this case with only authority, or only kin/friend, or only work relations. To illustrate: the structures in row 1 (P) consist of uniplex (“pure” or non-embedded) profit relations, i.e. the only resource that flows between the exchange partners consists of goods or services. The minimal unit in this class is a network consisting of one mutual profit tie (isolated unilateral profit ties do not exist in the data). A network with more than two actors who all are connected only by profit ties falls in this category but with third parties present.
Role structures in rows 2-6 represent cases in which a profit relationship occurs together with exactly one of the other types of relationship. In row 2 (A), all dyads are connected by authority and by a profit tie, where the profit may be mutual or unilateral; in the latter case, the direction of profit is opposite to the direction of authority; furthermore, none of the dyads are linked through a kin/friendship or work relation. Examples of role structure A are a case consisting of one dyad (no third party present) in which profit flows from a subordinate to a superior; and a case consisting of a chain of command, in which an actor has formal authority over another actor, who in turn has formal authority over a third party. Role structures W and K are similar, but now for the work and kin/friend relations, which are symmetric by definition. An example of role structure W with a third party is a triad in which profit flows from the agent to the client via the third party who has a horizontal work relation with the agent. Examples for role structure K with a third party, as proposed by Coleman (1990), are: (1) a guarantor structure in which the trustor has an informal tie to a third party, the third party has an informal tie to the trustee, and profit is transferred from trustor to the third party and from the third party to the trustee; (2) an advisor structure, which resembles the guarantor structure, but there is also a direct relation (e.g. profit) between trustor and trustee. Role structure (PA) is like structure (A), but in addition there is at least one dyad without an authority tie but with mutual profit exchange. Similarly, role structure (PK) is like structure (K), with in addition at least one dyad with only mutual profit exchange.
The remaining types contain compound role structures. A role structure is compound if it contains more than one type of relational model, comprising two, three, or four combinations of relations (Fiske, 2012). This means in our study that of the relations authority, work, and kin/friend, two or more are present, in addition to the profit relation. This presence can be multiplexity within the same dyad (e.g., a tie in which two kin actors have an authority relation and are involved in a corrupt exchange), or to concatenations of different types of ties across different pairs of actors, e.g., when two exchange partners are linked by a power relationship, and both are linked to a third party through a kin- or friendship relation. The most complex role structure is the compound (PAWK) combining all four relations of authority, kin-/friendship, work, and profit.
[1] Authority cannot go together with work (colleague), therefore the combinations of authority and work have three possible dyads null, asymmetric, and mutual, where asymmetric means authority and symmetric (mutual) means work. For combining profit and authority and work this implies 3×3=9 possibilities. However, the asymmetric dyads can go in the same or in opposite directions, adding a tenth possibility. This is then combined with the two values for friend/kin. Because these are symmetric and can have any combinations with profit, authority, and work, the grand total is 10 × 2 = 20.