Strategic supplier selection: the importance of process formality in non-automated supplier selection decisions

Abstract Industry 4.0 mainly focuses on the application of modern technologies (digitalization) and the changing role of human beings (digital transformation) in modern production and logistics systems. Besides the basic principles of digitalization, interconnectivity, and autonomization, the importance of human-centered decision-making processes, such as the selection of strategic suppliers, is also increasing, as complex, novel, and unstructured decisions cannot be fully computerized. In this context, there is still a lack of understanding of which formal patterns in the strategic supplier selection process will lead to better supplier performance. Until now, most of the literature emphasizes a minor number of process-related factors in the strategic supplier selection process leading to limited support for the individual decision-maker. This study introduces a cause-effect model that extends prior research by investigating the impact of process formality, as a comprehensive measurement construct of target-, information-, organization-, and heuristics-related process factors in the strategic supplier selection process on supplier performance and purchaser satisfaction. Based on the usage of variance-based structural equation modeling in a large-scale field study, a significant relationship between process formality and supplier performance as well as between process formality and purchaser satisfaction is substantiated.


Introduction
In the fourth industrial revolution era, cognitive work becomes more and more important. Operators of future manufacturing enterprises will be asked to perform more complex cognitive tasks inducing the need for advanced aid systems for complex decision support (Baumane-Vītoliņa et al., 2022;Rauch et al., 2020). Thereby, the strategic supplier selection process (SSSP) can be seen as one of the most important functions in a manufacturing enterprise to guarantee a reliable and cost-efficient supply of required materials and services for the production process (Arnolds et al., 2013;Irlinger, 2012;Zunk et al., 2020). Specifically, strategic suppliers play an important role in the core competencies of the company, the long-term sales and operations planning strategy, where the supplier is part of a long-time collaboration with the customer company (Durst, 2011;Zunk & Koch, 2014;Zunk et al., 2020). The SSSP can significantly influence the profit of a company and, therefore, is often considered as one of the main sources to gain a sustainable competitive advantage. Traditionally, the SSSP is focused on cost-, quality-as well as time-orientated targets (Arnolds et al., 2013;Cousins et al., 2002;Zunk & Schiele, 2011). Additional ones, like social, ecologic, environmental, and further targets, like the dependency reduction on a single source of supply, can be mentioned (Schulte, 2009).
Besides, to provide appropriate decision support for the SSSP, the following peculiarities of this domain should be considered: The SSSP consists of non-automated, as well as non-programmable decisions being mostly non-recurring, novel, politic/strategic, complex, and often unstructured. Therefore, the SSSP can be supported by applying heuristics and problem-solving techniques (Elbanna & Child, 2007;Pfohl, 1977;Riedl, 2012;Simon, 1966).
Strategic suppliers usually deliver a crucial product and/or service that can be hardly imitated by other suppliers (Schumacher, 2008) and are, or will be, a part of core-competence-based cooperation (Zunk, 2013;Durst, 2011;Zunk et al., 2020). In addition, in SSSP usually, a single decisionmaking process takes place, meaning that one single person/entity is responsible for the selection process (Buhrmann, 2010;Dyckhoff & Spengler, 2010;Kaufmann et al., 2014;Riedl, 2012).
Up to now, there is still a lack of understanding regarding which adequate formal behavioral patterns in the SSSP lead to better supplier performance. Dean and Sharfman (1993) investigated the relationship between the concept of procedural rationality and decision-making success. According to their results, managers who have systematically collected information achieved better outcomes. Subsequently, Kaufmann et al. (2012b) transferred the concept of procedural rationality to supplier selection decisions. The results showed a significant impact of procedural rationality on financial and non-financial performance. However, the concept of procedural rationality provides only limited support for the design of strategic supplier selection processes because it is mainly limited to the formal execution of information processing activities.
Most of the recent studies identified in the area of strategic supplier selection processes also tend to focus on a limited number of, mainly information-related, process factors in the SSSP, which limits the applicability of the established research findings in terms of process improvement and performance improvement. This paper extends the described information-related process factors in the SSSP by considering a multitude of target-related, organization-related, and heuristics-related factors that are derived from a literature review for the conceptualization of a comprehensive measurement construct for process formality.
Additionally, a high majority of decision support models for SSSP consider a limited number of economic-based factors for the evaluation of the supplier performance.
Therefore, this paper considers the impact of process formality on economic-based supplier performance factors in SSSP by investigating cost-based measures, as suggested by Kaufmann et al. (2012a), and extends the measurement model by incorporating additional quality-based and time-based measures.
Scientific literature further indicates the non-negligible importance of socio-psychological effects in terms of satisfaction and commitment (Pulles et al., 2016;Schiele et al., 2012;Steinmann & Schreyögg, 2000), which have not been frequently considered in decision support models for SSSP yet. Thus, the proposed research model includes socio-psychological process performance factors specified herein as a subjective measure of the purchaser regarding his satisfaction and commitment with the SSSP and his final supplier selection decision, defined as the purchaser satisfaction.
The remainder of the paper is organized as follows. The second section describes the theoretical foundation of this paper. The third section focuses on material and methods. The fourth and fifth sections report and discuss the results by answering the research questions and describing the implications, limitations, and future research directions.

The concept of process formality
The concept of process formality is defined as a set of reasonable, formalized, and standardized measures for adequate formal behavior in the SSSP. Thereby, the authors postulate that like production processes, SSSP can be improved by using controlled interactions in the course of decision-making procedures (Klein & Scholl, 2011;Pfohl, 1977). By conducting a literature review, the authors identified 73 pertinent studies for the conceptualization of the process formality. Moreover, the categorization of the identified studies is based on a grounded theory approach (Böhm, 2000;Breuer, 2010) where the authors defined and coded categories by importing qualitative data, creating preliminary categories, reviewing their convergent or divergent relationships, and redefining the final categories within a circular approach (Equit & Hohage, 2016). Table 1 summarizes the categorizations and findings from the analyzed scientific literature.
According to Table 1, only a handful of studies were assigned to the first cluster of "targetrelated process factors". The identified studies focus on the degree of precision of the target system, and the continuous usage of this target system during the SSSP. Most of the identified studies were assigned to the second cluster of "information-related process factors" which relate to the intensity of information supply and information processing activities in the SSSP. In addition, the third cluster was defined as "organization-related process factors". This cluster measures the level of systematically organized process activities in the SSSP. The remaining studies were assigned to the fourth cluster of "heuristics-related process factors" which investigates the processing of logical problem-solving procedures during the SSSP. Moreover, the authors identified a set of research studies that are mainly based on information-related variables but tend to include additional influencing process factors. These studies were assigned to the cluster "multidimensional research studies".
Most of the identified studies cannot provide extensive answers for the comprehensive understanding of adequate formal behavioral patterns in the SSSP because they primarily focus on isolated or mainly information-based process factors. Literature shows that the consideration of unidimensional process factors does not always have a significant positive impact on the performance outcomes thus increasing the need for more extended models. Therefore, this study comprises the identified target-related, information-related, organization-related, and heuristicsrelated process factors into a comprehensive measurement construct for the process formality.

The concept of supplier performance
The concept of supplier performance considers economic-based factors for the evaluation of SSSP outcomes. According to the literature, the authors conclude that the effects of decision-making procedures in business organizations can be measured on 1) the supply chain level, 2) the company level, 3) the department level, and 4) on the level of the individual entity. Acharya (2012) introduces a set of measures on the supply chain level while researchers like Schenkel (2006) focus on the market success on the company level as an external measure combined with the company-internal efficiency. Moreover, Hsu et al. (2008) recommend the measurement of the financial and the overall performance of the company, and Wentzel (2002) used the managerial performance and the budgetary performance in his measurement approach.
On the level of the individual supplier, the supplier performance is mainly measured by cost-based indicators. Kaufmann et al. (2012a) investigate the financial decision effectiveness by measuring total costs, actual costs, price stability, and the meeting of target costs during the supplier transactions. More holistic approaches tend to incorporate additional measures to establish a multi-dimensional construct of supplier performance. Buhrmann (2010) used the non-financial decision effectiveness which includes quality-and time-based measures, and the financial decision effectiveness which includes cost-based measures of the supplier performance. A similar approach is used by Kaufmann

Main findings
Target-related process factors Hauschildt (1988) emphasizes the importance of target systems in decision-making processes. In decision-making processes, specific target systems do not automatically exist and must therefore be created by using a process of target formulation to fit the overall targets of the enterprise. Researchers like Conant and White (1999), Dyson and Foster (1982), Kenis (1979), Neuert (1987), and Schenkel (2006) show a significant relationship between the formalization of targets in decision-making processes and various efficiency-related measures. Claycomb et al. (2000) highlight a clear interaction between the degree of formalization in decision-making processes and the market performance respectively the financial performance. According to Geißler (1986), a missing definition of targets can be the starting point of failures by causing constitutional, procedural, and personal problems in decision-making processes. Riedl (2012) identifies a significant relationship between the determination of relevant decision criteria before the supplier selection as part of a decision process decomposition strategy, which is linked to the residual uncertainty that affects the supplier's strategic capabilities and the financial supplier performance. Buhrmann (2010) acknowledges a significant impact of the decision task decomposition variable, on the nonfinancial decision effectiveness respectively on the financial decision effectiveness. Thereby, the decision task decomposition variable includes the determination of relevant decision criteria, the splitting of the decision into smaller pieces, and the determination of specifications before the supplier selection.
Information-related process factors Theoretical discussions regarding the conceptualization of information-related process factors were conducted by Bourgeois and Eisenhardt (1988), Segars and Grover (1998), Dyson and Foster (1982), Greenley and Bayus (1993), Premkumar and King (1994), and Wild (1982). Bronner et al. (1972) have investigated that participants in laboratory experiments never used all theoretically available information. The investigations by Cramme (2005) show a significant correlation between the information demand activities, coming from personal resources (e.g., suppliers) and the decision-making efficiency. Moreover, the results show no significant correlation between the information demand activities from impersonal resources (e.g., market data) and the decision-making efficiency. The studies by Witte (1988;1972a;1972b;1972c) provide valuable, but sometimes controversial insights. For example, the researchers found no significant relationship between the information demand and supply activities and the efficiency of the decision-making processes. However, further studies, e.g., Molloy and Schwenk (1995), Moon et al. (2003), Premkumar and King (1992), Venkatraman and Ramanujam (1987), demonstrate a significant correlation between the usage of information technology and reference processes generally and an increase in the decisionmaking performance.

Main findings
Organization-related process factors Some basic conceptualizations of organizational activities in decision-making processes can be found in the studies by Pfohl (1977), Grover and Segars (2005), Segars and Grover (1998), and Venkatraman and Ramanujam (1987). Joost (1975) notes that organizational activities are distributed over the whole duration of the decision-making process. Increased organizational activities will lead to higher transparency and higher efficiency in decisionmaking processes. John and Martin (1984) postulate that the organizational structure significantly influences the credibility and utilization of planning and decision-making activities. Langley (1989) states that the formal analysis of problem-solving processes acts as glue within the interactive processing of the necessary process activities, generating organizational commitment, and ensuring continuing action. Schenkel (2006) postulates that the clarification of frameworks and tasks as well as the personal and temporal assignment of tasks need to be perceived as indicators of the formal quality which directly affects the quality of the planning process.
Heuristics-related process factors Theoretical investigations, e.g., Moon et al. (2003), Wild (1982), Bourgeois and Eisenhardt (1988), and Pfohl (1977), recommend the usage of heuristics, reference processes, and reference models in managerial planning and decision-making activities. For Buhrmann (2010), both the prioritization of evaluation criteria and the assignment of weight before the supplier evaluation are part of the concept of the decision task composing variable which significantly impacts the non-financial decision effectiveness (e.g., quality targets) respectively the financial decision effectiveness (e.g., total costs). Riedl (2012) defines the prioritization of evaluation criteria and the assignment of weight before the supplier evaluation as part of his conceptualization of the decision process decomposition which significantly affects the residual uncertainty leading to increased supplier´s strategic capabilities and better financial supplier performance. Additional studies, e.g., Neuert (1987) and Elbanna and Child (2007), note a positive relationship between the application of problem-solving techniques and decision-making efficiency. According to Klein and Yadav (1989), it should be noted that the number of dominant alternative solutions significantly affects the choice accuracy and the choice effort. (Continued)

Main findings
Additional multi-dimensional research studies Dean and Sharfman (1993) introduced the concept of procedural rationality, which is primarily based on information-oriented measures. Their results indicate that managers who have systematically collected information and used analytical techniques were more effective than those who did not (Dean & Sharfman, 1996;Dean & Sharfman, 1993). Elbanna and Child (2007) share this view, stating that procedural rationality has an impact on organizational performance. Acharya (2012) investigated that procedural rationality did not have any effect on the total costs of the supply chain, but the interaction of information availability and procedural rationality influenced the overall supply chain performance. In recent studies, Kaufmann et al. showed a significant impact of procedural rationality on financial as well as non-financial performance (Kaufmann et al., 2012b). Moreover, Kaufmann et al. (2014) found that procedural rationality in sourcing teams enhances cost performance. Additional significant effects of procedural rationality in supplier selection decisions were identified for the reduction of residual uncertainty in Chinese and US samples on the financial and non-financial performance (Kaufmann et al., 2014). Besides procedural rationality, the heuristics-based concept of (decision) comprehensiveness by Fredrickson (1984Fredrickson ( , 1983) is one of the most frequently applied approaches in decision-making research. Fredrickson and Iaquinto (1989) found that changes in organizational size, executive team tenure, and the level of team continuity were associated with changes in comprehensiveness. In another study, Atuahene-Gima & Li, 2004) discovered a positive relationship between comprehensiveness and new product performance, while Nooraie (2008) demonstrated that the decision magnitude is significantly associated with the level of comprehensiveness in the decision-making process. Similarly, Simons et al. (1999) pinpoint that comprehensiveness partly moderates the relationship between team diversity variables and financial performance.
et al. (2012b) by measuring the cost-based supplier financial performance together with the qualityand time-based supplier non-financial performance. Moreover, Riedl (2012) investigates the costbased financial supplier performance and the supplier´s technical-, innovation-, management-, service-, and financial-strength-based strategic capabilities. Other studies measured the cost-based supplier financial performance and the quality-and time-based supplier non-financial performance (Kaufmann & Carter, 2006;Kaufmann et al., 2014;Riedl et al., 2013).
This study introduces a cause-effect model that extends prior research by investigating the impact of process formality, as a comprehensive measurement construct of target-, information-, organization-, and heuristics-related process factors in the strategic supplier selection process on supplier performance and purchaser satisfaction. After introducing the concept of process formality, the supplier performance as the economic-based evaluation of the outcomes of the SSSP is focused on the usage of cost-based measurement indicators that will be measured based on predefined targets in comparison to actual economic-based outcomes (Staehle et al., 1999;Wild, 1982). Moreover, the proposed model will include further measures, in particular, quality-and time-dimensions to establish a more comprehensive construct of the supplier performance.

The concept of purchaser satisfaction
The concept of purchaser satisfaction will be used to measure the socio-psychological effects of the SSSP, which have not been frequently considered in the literature. However, the subjective satisfaction of the purchasing managers can be seen as the driving force behind specific actions in the SSSP, which is based on subjective estimation of the process outcomes (Pulles et al., 2016;Schiele et al., 2012;Steinmann & Schreyögg, 2000). Neuert (1987) refers to the concept of personal efficiency which measures the satisfaction of the decision-maker in terms of process satisfaction and identification with the achieved results. Therefore, other studies, recommend the usage of standardized self-rating scales (Brouër, 2014;Chong & Chong, 2002;Gul et al., 1995). Moreover, researchers like Piercy and Morgan (1990) and Schenkel (2006) measure the satisfaction with the established plan, while researchers like Juga et al. (2010), Saura et al. (2008), and Zhang et al. (2005) turn to various dimensions of the service satisfaction or customer satisfaction as a set of socio-psychological indicators for the outcomes of the decision-making processes. In addition to the economic-based evaluation of the outcomes of the SSSP which will be measured by the supplier performance, this study introduces the purchaser satisfaction as a measure for the socio-psychological evaluation of the outcomes of the SSSP. Thereby, the authors consider the satisfaction and commitment of the individual purchasers with the SSSP and with their final supplier selection decision.

Hypothesis development
In this section, the authors develop the basic hypotheses for the subsequent investigation of SSSP in manufacturing companies. In line with the literature review, the authors propose that the fulfillment of formal behavioral patterns in the strategic supplier selection process has a significant influence on the supplier performance.
Unfortunately, up to now, only a handful of studies were conducted in the specific areas of purchasing and supply management. Kaufmann et al. (2016); (2012b) used the concept of procedural rationality by Dean and Sharfman (1996); Dean & Sharfman (1993) to investigate the effects on financial as well as non-financial performance in single supplier selection decisions (Kaufmann et al., 2012b). In a follow-up study, Kaufmann et al. (2014) further showed a significant effect of procedural rationality on cost performance and quality-/delivery-/innovativeness performance in sourcing teams. Moreover, a multitude of valuable studies for the development of our hypothesis and underlying constructs were found in strategic management. In this context, the models identified, investigate the effects of certain rationality-orientated behavioral patterns, e.g., the comprehensives (Fredrickson, 1984), the degree of rational planning behavior (Neuert, 1987), the quality of planning (Pulendran et al., 2003), etc., in decision-making processes on performance measures, like organizational/business performance (Elbanna & Child, 2007;Goll & Rasheed, 2005Papke-Shields et al., 2006;Pulendran et al., 2003;Schenkel, 2006) new product performance (Nooraie, 2008), financial performance (Simons et al., 1999), and overall efficiency (Neuert, 1987).
In this study, the authors postulate that the fulfillment of formal behavioral patterns in the SSSP, measured by the process formality (PF), has a significant impact on the supplier performance (SP). Moreover, the developed research model investigates the relationship between the process formality (PF) in the SSSP and socio-psychological process performance factors, measured by the purchaser satisfaction (PS).
Therefore, the hypotheses to be tested in our research are formulated as follows: Hypothesis 1. The process formality has a significant impact on supplier performance in the strategic supplier selection process.
Hypothesis 2. The process formality has a significant impact on purchaser satisfaction in the strategic supplier selection process.

Sample and data collection
The empirical study focuses on the investigation of the cause-effect relationships in SSSP in manufacturing enterprises. Thereby, the selection of key informants is regarded as one of the most crucial factors that influence the validity of the established research results (Bortz & Schuster, 2010;Kumar et al., 1993). The contact to the units of analyses "purchasing managers in manufacturing enterprises in Central-Europe" was established by using the following three membership directories of logistics and purchasing organizations: BVL (Bundesvereinigung Logistik), BMOE (Bundesverband Materialwirtschaft, Einkauf und Logistik), and MUL (Montanuniversitaet Leoben). Moreover, based on the "NACE" industrial branch classification system, the authors defined manufacturing enterprises as specialized companies that are mainly machine-based and produce larger quantities of goods and services within a specific timeframe, based on the economic division of labor (Dyckhoff & Spengler, 2010;NACE, 2020).
In line with the research design of previous research studies, the participants were asked to recall a specific strategic supplier selection process from the past, which fulfilled the following criteria: The process was conducted within the last twelve months, and the final decision was made by themselves, they were able to assess the supplier performance in terms of price, quality, and time measures, the final decision was not clear in the very beginning, the required purchasing object was a material which was strategically important for the corporate success of the company (Kaufmann et al., 2012b(Kaufmann et al., , 2014(Kaufmann et al., , 2016Riedl, 2012;Riedl et al., 2013).
The authors used a field study as a research method and a questionnaire-based survey as a method of data collection. The standardized questionnaire was developed by using state-ofthe-art guidelines for empirical research studies (Kirchhoff et al., 2010;Moosbrugger & Kelava, 2012;Porst, 2011) and pre-tested by 23 specialists working in the field of strategic supplier selection processes.
By combining the signed members of the membership directories, the authors generated a list of 3,975 purchasing managers. The final sample consisted of 206 fully completed questionnaires leading to a response rate of 5.2% for the subsequent statistical analyses. The operationalization of the variables is based on the guidelines by Esser (Schnell et al., 2011) for the selection and/or the development of appropriate indicators. In this research, the authors primarily used reflective measurement constructs by using a five-point Likert scale (Cooper & Schindler, 2014). Table 2 displays the variables and measurement items.

Supplier performance
The authors defined the first dependent variable supplier performance as a holistic construct that included a set of economic-based measures. Therefore, the outcomes of the strategic supplier selection process will be investigated by measuring the supplier performance based on costs, price stability, delivery time, and quality indicators (Buhrmann, 2010;Kaufmann et al., 2012bKaufmann et al., , 2014Riedl, 2012).

Purchaser satisfaction
In the model, the second dependent variable was conceptualized as a subjective measure of the supply manager regarding their satisfaction and commitment with the SSSP and with the final strategic supplier selection decision. The purchaser satisfaction was measured based on a set of socio-psychological indicators as an additional measurement variable for the outcomes of the SSSP (Pulles et al., 2016;Schiele et al., 2012;Neuert, 1987;Schröder, 1986;Bronner, 1973).

Results
In this section, the authors analyze the results of the statistical procedures that were computed by using IBM ® SPSS ® Statistics v.27 for the descriptive analysis and SmartPLS ® v.3.3.2 for the structural equation modeling procedures.

Biases tests
As suggested by Armstrong and Overton (1977), the authors tested the non-response bias by evaluating the representability based on significant differences in earlier and later responses. The conducted ANOVA showed no significant differences in all indicator values between "earlier", "average", and "later" received survey responses. This can be seen as another indication of the representability as well as the external validity of the research results.
Moreover, the so-called recalling information bias (Kaufmann et al., 2012b;Srinivasan & Ratchford, 1991) was evaluated by using a T-test. The results showed no significant differences in all indicator values between "recently conducted" and "more elapsed" SSSP.

Evaluation of the measurement model
For the evaluation of the measurement model, the authors computed Cronbach´s alpha (CBA) values resulting in 0.905 for the PF, 0.921 for the SP, and 0.855 for the PS. All of them are above the recommended value of 0.600 respectively 0.700 and, thus, ensure internal consistency reliability Heath & Jean, 1997).
Moreover, the authors consider the composite reliability (CR) as a second measure of internal consistency reliability. The computed values come out at 0.921 for the PF, 0.935 for the SP, and 0.911 for the PS. All computed values are above the recommended limit of 0.700 which further confirms the internal consistency reliability of our measurement model (Fornell & Larcker, 1981;Hair, 2014;Peter, 1979). In the next step, the indicator reliability was computed. Table 3 displays the indicator loadings. According to the literature, the recommended values for the indicator loadings should not be below 0.400 (Homburg & Baumgartner, 1995;Krasnova et al., 2008). If the indicator reliability is between 0.400 and 0.700, it should only be optimized if the deletion of an indicator leads to an increase in both the composite reliability and the average variance extracted. Ideally, the indicator reliability should be above 0.700 (Hair, 2014). However, all indicators investigated showed values above the recommended threshold in the field study and, therefore, they can be considered as reliable.
In the next step, the average variance extracted (AVE) was calculated. In our case, the AVE values are 0.518 for the PF, 0.645 for the SP, and 0.773 for the PS. All values are above the minimum criteria of 0.400, (Bagozzi & Youjae, 1988) and above the more conservatively defined value of 0.500 (Hair, 2014;Hair et al., 2014) which ensures the convergent validity of the research model. Discriminant validity I was evaluated by computing the cross-loadings. Literature suggests that an indicator's outer loading on the associated variable should be greater than any of its crossloadings (Hair, 2014). This was the chase for all indicators. The computed results thus confirm the discriminant validity of the research model. Discriminant validity II was assessed by concerning the Fornell-Larcker criterion. According to the literature, the square root of each construct's average variance extracted (AVE) values should be greater than its highest correlation with any other construct (Hair, 2014). This holds for all the computed values, therefore further confirming the discriminant validity of the research model. In addition, the Heterotrait-Monotrait Ratio (HTMT) is generated as a third measure for the discriminant validity. The calculations result in the following values: PF→SP: HTMT = 0.628, PS→SP: HTMT = 0.796, PS→ PF: HTMT = 0.661. All values are below the recommended value of 0.850, (Hair, 2014) with this third value confirming the discriminant validity of the underlying research model.
In the last step, the authors calculated the indicator significance. As displayed in Table 3, all indicator values are significant and, therefore, below the recommended p-value of 0.050 (Gefen & Straub, 2005).

Evaluation of the structural model
In the first step, the authors computed the significance of the path coefficients. The results show a highly significant path coefficient for the PF on the SP and a highly significant path coefficient for the PF on the PS. This means that the proposed cause-effect relationships are confirmed in the structural model of the field study (Bortz & Schuster, 2010). Moreover, the values regarding the size of the path coefficients are positive (0.579 for PF→SP respectively 0.603 for PF→PS) therefore in line with the proposed relationships. In addition, the calculated coefficients of determination (R 2values) show positive and moderate values (Hair, 2014). In detail, the results are R 2 -value for the SP = 0.335, and R 2 -value for the PS = 0.364. Moreover, the calculated effect size (f 2 ) shows a large effect (f 2 = 0.503) for the relationship between the PF and the SP and a large effect (f 2 = 0.572) for the relationship between the PF and the PS (Cohen, 1988;Hair, 2014).
The predictive relevance of the research model is thus ensured. For an additional assessment of discriminant validity, the authors calculated the collinearity statistics (VIF). Thereby, all resulting values are higher than the recommended minimum value of 0.200 and lower than the recommended maximum value of 5.000 which again confirms the discriminant validity of the research model (Hair, 2014;Kock & Lynn, 2012).
The authors calculated the standardized root mean squared residual (SRMR) for the composite model. In this case, the SRMR value is 0.071 which, according to literature recommendations (Hair, 2014;Hu & Bentler, 1999), can be considered as a good model fit.

Evaluation of the proposed cause-effect relationships
As displayed in Figure 1, the results of the structural equation modeling calculations show a highly significant relationship (p-value = 0.000) between the PF and the SP. Hence, hypothesis 1 is confirmed, meaning that there is a significant impact of the process formality (PF) in SSSP on the cost-, time-, quality-based strategic supplier performance, defined as the supplier performance (SP).
Moreover, the results of the structural equation modeling calculations show a highly significant relationship (p-value = 0.000) between the PF and the PS. Hypothesis 2 is thus confirmed, meaning that there is a significant impact of the process formality (PF) in SSSP on the purchaser satisfaction (PS), introduced as a subjective measure of the supply manager regarding their satisfaction and commitment with the SSSP and with the final strategic supplier selection decision.

Discussion of the research findings
This research contributes to the body of knowledge by enhancing the understanding of which formal behavioral patterns in the SSSP will ultimately lead to better supplier performance and higher purchaser satisfaction.
In a first step, the authors conceptualized a latent construct "process formality" in SSSP which goes beyond the actual state-of-the-art concepts and theories of rational behavior in decision-making processes named procedural rationality (Acharya, 2012;Kaufmann et al., 2014;Dean & Sharfman, 1996), rational processing (Kaufmann et al., 2016), and decision comprehensiveness (Atuahene-Gima & Li, 2004;Fredrickson, 1983;Nooraie, 2008), etc. This was done by comprising target-, information-, organization-, and heuristics-related process factors into a comprehensive measurement model. Based on the behavioral decision-making theory, a multitude of studies was transferred from marketing, strategic management, logistics and operations management as well as supply chain management to the area of supply management. Overall, the developed process formality measurement model comprises a list of 11 multi-dimensional items that were validated by using data from manufacturing enterprises in Central-Europe.
The empirical data confirmed a positive and highly significant relationship between process formality and the supplier performance (γ1 = 0.576, p-value = 0.000, R 2 = 0.331). The findings confirm the hypothesis that the degree of process formality in the SSSP positively affects the overall supplier performance measured by a set of cost-, quality-and time-based indicators. In line with previous studies, this research result hights the importance of formal behavioral patterns in SSSP processes (Kaufmann et al., 2012b(Kaufmann et al., , 2014(Kaufmann et al., , 2016. Furthermore, the empirical data confirmed a positive and highly significant relationship between process formality and purchaser satisfaction (γ2 = 0.601, p-value = 0.000, R 2 = 0.362). This confirms the hypothesis that the degree of process formality, as a measure of formal behavior, in the SSSP

Figure 1. Model evaluation (p-Values).
positively affects the satisfaction and commitment of the purchasing manager regarding the execution of the SSSP and the final supplier selection decision. To the best of our knowledge, this has not been considered in the literature yet and thus it can be considered as another novel result of this study.
It can be stated that controlled interactions, which are based on the concept of process formality will have a significant impact on the overall-strategic supplier performance, and on socio-psychological aspects, like the satisfaction and commitment of the purchaser. Thereby, the concept of process formality includes the degree of precision of the target system and the continuous usage of the target system in the course of the SSSP and during the final strategic supplier selection decision, the intensity of search activities for decision-relevant information, the maturity level of systematically organized activities, and the application of heuristics in the SSSP.
From a methodological point of view, this research study applied state structural equation modeling for the multivariate investigation of the proposed cause-effect relationships. These techniques deliver a multitude of valuable insights, e.g., in terms of enhanced validity, reliability, and overall model fit measures which, in contrast to most of the existing studies in supply management which are mainly based application of more "conservative" statistical methods, can be seen as another benefit of this research study.
Moreover, the selected sample is comprising a heterogeneous setting of manufacturing enterprises from different industrial sectors, e.g., metal, wood, automotive, chemicals, etc. Therefore, the provided instruments can be used in cross-sector studies, as well.

Limitation of the research study
Our research investigates the impact of process formality on supplier performance as well as on purchaser satisfaction within the scope of the individual supplier. As such, this research does not address the impact of process formality on the companies´ performance or the overall performance of the entire supply network.
Moreover, this research focuses on the individually performed SSSP, and therefore, group processes are not considered. Furthermore, our research is limited to the industrial sector of manufacturing enterprises in Central-Europe which limits the transferability of the established research findings in terms of potential cross-cultural differences.

Implications
Based on the holistic approach of this study, future research has to continue the development of the descriptive decision-making theory by transferring insights from subject-related disciplines to the specific field of the SSSP in manufacturing enterprises which, in the end, should contribute to establishing a more comprehensive theory of supply management. Moreover, in the opinion of the authors, there lies a considerable potential in the application of behavioral theories in supply management and related fields like logistics, operations management, and supply chain management. Besides the in-depth investigation of cause-effect relations between the process formality and various performance constructs, further research should also focus on the company-internal and company-external determinants as well as situational, contextual, and personal variables in SSSP. Thereby, the further investigation of cultural variables and complex group decision-making approaches might play an important role in future supply management research (Stek et al., 2022). Especially in the context of modern Industry 4.0 applications, research should, therefore, also take a specific focus on the investigation of the future role of human beings in smart and sustainable ecosystems (Woschank et al., 2021b(Woschank et al., , 2022a. Accordingly, recommendations for action at the company level as well as for vocational training and continuing education at the tertiary level and in the in-company continuing education of future experts will be outlined.

Recommendations for actions at the company level
Management should design and implement a structured SSSP to increase supplier performance based on the developed and empirically validated concept of process formality. Based on the research findings, managers can develop computer-based and/or manual support systems (e.g., handbooks, checklists, guide booklets) for the SSSP. For a comprehensive improvement of the SSSP, the authors strongly recommend considering all the elements of process formality to reach an increased supplier performance. Thus, it is important to recognize that an isolated focus (e.g., the increase of the information quality in the SSSP), will only be partially helpful. Furthermore, the authors highly suggest considering motivational elements (e.g., satisfaction and commitment) as integral aspects in the SSSP (Weller et al., 2021;Zunk, 2015;Zunk et al., 2013). The supply manager´s motivation plays an important role in the SSSP (e.g., especially in the development of the target system, during the information search as well as information processing activities) and during the final supplier selection decision.
Based on the empirical findings of our study, the authors recommend that practitioners should introduce and conduct regular and continuous strategic supplier selection training processes for supply managers. These should concern the phases, planning, instruments, heuristics, and personnel of the SSSP in manufacturing enterprises. This could be implemented, for example, via the development and introduction of short and phased modularized measures, also called microcredentials (Woschank & Pacher, 2020a;2020b;2020c).

Recommendations for action in tertiary vocational education and training
The competencies required in the context of SSSP in manufacturing enterprises should also be reflected in the relevant competency profiles of the university to be able to integrate competency development and promotion actively and transparently into the curricula Ralph et al., 2022). The authors further recommend the application of laboratory experiments to investigate human behavior in supply management processes . This significantly underrated research method should be used as an additional tool for the development of decision-making research by allowing the researcher to design specific frameworks that eliminate possible confounding variables (Deck & Smith, 2013;Kompatscher et al., 2021;Woschank & Pacher, 2020d).
Universities must create more awareness for the SSSP respectively for strategic planning and decision-making processes in general by developing more accurate education programs. Therefore, the multidisciplinary approach on how to integrate and deal with SSSP concepts from the different angles of the respective disciplines is essential (Ralph et al., 2022;Zunk, 2018;Zunk & Sadei, 2015). Moreover, universities should provide opportunities to learn and develop problembased behavior in managerial planning and decision-making processes to connect theoretical concepts with practical applications (Ralph et al., 2021;Woschank et al., 2021a).

Conclusions
In a nutshell, this paper investigates which formal behavioral patterns in the strategic supplier selection process (SSSP) in manufacturing enterprises lead to improved supplier performance (SP) and higher purchaser satisfaction (PS). Therefore, the authors propose a latent construct named process formality (PF) incorporates which goes far beyond actual state-of-the-art concepts by identifying target-, information-, organization-, and heuristics-related process factors to empirically substantiate its impact on SP and PS. Therefore, the paper provides a novel elaboration of theoretical constructs and, later on, the empirical substantiation regarding the composition as well as the temporal, personal, and content-relation design of supplier selection processes in manufacturing enterprises, also in a practice-focused intention. Using a large-scale questionnaire distributed to central European purchasing managers, where empirical research is particularly scarce, the two hypotheses were tested and confirmed. A positive and highly significant relationship between process formality and supplier performance was found, confirming the hypothesis that the degree of the process formality in the SSSP positively affects the overall supplier performance measured by a set of cost-, quality-and time-based indicators. Moreover, the research confirmed the hypothesis that process formality positively affects the satisfaction and commitment of the purchasing manager regarding the execution of the SSSP and the final supplier selection decision. As a result, motivational elements like purchaser satisfaction and purchaser commitment to the formal supplier selection procedures should not be neglected. Finally, for a realignment of the changing role of the human being in modern manufacturing enterprises, this paper further provides empirically-confirmed evidence for training initiatives based on the investigated and corroborated major success factors in the strategic supplier selection process, identified as the constitutional elements of the process formality.