WIT Transactions on Information and Communication Technologies, Oct 14, 2003
In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various ... more In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various aspects of customer purchase behavior. However, to date, the applications of the technique have mainly focused on improving algorithms for detecting sequentially related events, whereas the implications of the sequences, and their incorporation into a global structure of consecutive sequences have been treated to a lesser extent. In this paper, such a structure, that we will refer to as sequential architecture, will be empirically investigated for a specific case in a fast moving consumer goods setting. Hence, the goal of this paper was to introduce a new concept that might prove to be a relevant tool for marketing decision making rather than offering a sound solution within a clearly demarcated problem definition. As opposed to the traditional sequence-analysis approaches, in this study, an array of binary Iogit analyses was applied for detecting significant sequences among category purchases. We use the output of the Iogit analyses to define the category that is most significantly influenced per newly purchased catego~, and we select these links for constructing the applicable sequential architecture. Finally, we provide empirical evidence that the methodology suggested is able to double the performance of predicting purchases in categories that were not purchased previously by the consumer, compared to a random model. In summary, we have shown that (i) binary logit analysis provides a feasible alternative for detecting and selecting highly significant sequential relationships, (ii) a sequential architecture can be successfully compiled through the methodology offered in this paper, and (iii) the provided sequential architecture can be a useful tool in understanding and predicting customer behavior. Future applications possibly lie ahead in the field of inter-category management, shelf-space allocation, store-layout decisions, retailer promotions, customer profiling and individual customer predictions.
International Conference on Data Mining, Sep 10, 2002
Response modeling is a very important application field of classification methods in direct marke... more Response modeling is a very important application field of classification methods in direct marketing because the success of a direct-mail campaign is highly dependent on who is being targeted. To date, standard classification models are applied to predict future purchasing behaviour for the complete customer file. In practice, however, companies use mailing budgets, i.e. only a subset of customers will be sent mail. Just those customers with sufficiently high-expected response rates are mailed to. The percentage of the total population that will actually receive the mailing is referred to as mailing depth. Hence, the real classification problem is not to classify all potential recipients as well as possible, but rather to find those customers, within the budget limitation, with the highest probability of response. Therefore, we propose an innovative alternative route to improved overall performance by tailoring the classification method to fit the problem at hand. We adapt binary logistic regression by iteratively changing the true values of the dependent variable during the maximum-likelihood estimation procedure. Those customers who rank lower than the cutoff in terms of predicted purchase probability, imposed by the mailing-depth restriction, will not contribute to the total likelihood. We illustrate our procedure on a real-life direct-marketing dataset comparing traditional response models to our innovative approach optimizing for a specific mailing depth. The results show that for mailing depths up to 48°/0 our method achieves significant and substantial profit increases.
Most analyses in marketing assume data to be either nominal or interval level. However, in many c... more Most analyses in marketing assume data to be either nominal or interval level. However, in many cases the data represent ordinal properties. Ranking data have been analysed in many disciplines using a wide range of methods, including distance-based models. Standard methods (eg ...
Here we introduce a web mining approach for automatically identifying new product ideas extracted... more Here we introduce a web mining approach for automatically identifying new product ideas extracted from web logs. A web log - also known as blog - is a web site that provides commentary, news, and further information on a subject written by individual persons. We can find a large amount of web logs for nearly each topic where consumers present their needs for new products. These new product ideas probably are valuable for producers as well as for researchers and developers. This is because they can lead to a new product development process. Finding these new product ideas is a well-known task in marketing. Therefore, with this automatic approach we support marketing activities by extracting new and useful product ideas from textual information in internet logs. This approach is implemented by a web-based application named Product Idea Web Log Miner where users from the marketing department provide descriptions of existing products. As a result, new product ideas are extracted from th...
Response modeling is a very important application field of classification methods in direct marke... more Response modeling is a very important application field of classification methods in direct marketing because the success of a direct-mail campaign is highly dependent on who is being targeted. To date, standard classification models are applied to predict future purchasing behaviour for the complete customer file. In practice, however, companies use mailing budgets, i.e. only a subset of customers will be sent mail. Just those customers with sufficiently high-expected response rates are mailed to. The percentage of the total population that will actually receive the mailing is referred to as mailing depth. Hence, the real classification problem is not to classify all potential recipients as well as possible, but rather to find those customers, within the budget limitation, with the highest probability of response. Therefore, we propose an innovative alternative route to improved overall performance by tailoring the classification method to fit the problem at hand. We adapt binary l...
This study focuses on the importance of mission valence and how public organisations can stimulat... more This study focuses on the importance of mission valence and how public organisations can stimulate a mission-oriented culture. More precisely, structural equation modelling was used to analyse a sample of 585 non-managerial employees employed by a public welfare organization with the aim of testing if (1) goal clarity, public service motivation and work impact are related with higher levels of mission valence, and (2) how communication with specific organizational sources influence these relationships. The study results indicate that goal clarity, public service motivation and work impact are positively related with mission valence.. In addition, the study results indicate that transformational leadership and co-workers influence perceptions of goal clarity, public service motivation and work impact. However, despite the fact that supervisors are often depicted as an interface between the individual and the organization, the study results indicate that supervisors influence goal cla...
In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various ... more In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various aspects of customer purchase behavior. However, to date, the applications of the technique have mainly focused on improving algorithms for detecting sequentially related events, whereas the implications of the sequences, and their incorporation into a global structure of consecutive sequences have been treated to a lesser extent. In this paper, such a structure, that we will refer to as sequential architecture, will be empirically investigated for a specific case in a fast moving consumer goods setting. Hence, the goal of this paper was to introduce a new concept that might prove to be a relevant tool for marketing decision making rather than offering a sound solution within a clearly demarcated problem definition. As opposed to the traditional sequence-analysis approaches, in this study, an array of binary Iogit analyses was applied for detecting significant sequences among category purchases. We use the output of the Iogit analyses to define the category that is most significantly influenced per newly purchased catego~, and we select these links for constructing the applicable sequential architecture. Finally, we provide empirical evidence that the methodology suggested is able to double the performance of predicting purchases in categories that were not purchased previously by the consumer, compared to a random model. In summary, we have shown that (i) binary logit analysis provides a feasible alternative for detecting and selecting highly significant sequential relationships, (ii) a sequential architecture can be successfully compiled through the methodology offered in this paper, and (iii) the provided sequential architecture can be a useful tool in understanding and predicting customer behavior. Future applications possibly lie ahead in the field of inter-category management, shelf-space allocation, store-layout decisions, retailer promotions, customer profiling and individual customer predictions.
This study contributes to our understanding of how organizations can craft a mission-based cultur... more This study contributes to our understanding of how organizations can craft a mission-based culture by examining the relationship between mission valence, PSM, goal clarity and work impact. More specifically, the study assesses how value-laden communication with multiple intraorganizational socialization referents is related with the cited variables. The developed hypotheses are tested using structural equation modelling and a sample of 585 non-managerial employees employed by a public welfare organization. The findings confirm Wright et al.'s (2012) claim that position in an organizational hierarchy is not likely to influence the analyzed relationships. The magnitude of the relationships, however, diverges. In contrast to previous research, the study results indicate that, in the case of lower level employees, PSM is the most powerful predictor of mission valence. Furthermore, the results indicate that exposure to organizational values via interaction with internal socialization agents is positively related with their perceived importance. The results thus not only confirm the relevance of incorporating the institutional setting when analyzing mission valence but also provides further proof for an institutional theory of PSM by highlighting that different organizational socialization agents could play a distinctive role in crafting PSM and a mission-based culture.
Given the lack of insights into the micro-determinants of strategic planning (SP) in public organ... more Given the lack of insights into the micro-determinants of strategic planning (SP) in public organizations, this study uses information-processing theory and self-efficacy theory to investigate individual-level predictors of commitment to strategic plans among planning team members (PTMs). Specifically, we investigate whether plan commitment is contingent upon the fit between PTMs' preferred way of information-processing (i.e. their cognitive style) and the information-processing characteristics underlying SP processes in public organizations. Based on data gathered with 439 PTMs from 203 Flemish municipalities, we find that PTMs with a creating and planning style are committed to strategic plans because they deem SP useful.
Working Papers of Faculty of Economics and Business Administration Ghent University Belgium, 2009
Convinced that it will improve their performance, the majority of public and non-profit organizat... more Convinced that it will improve their performance, the majority of public and non-profit organizations has developed a formal mission statement. However, despite its popularity, the assumed mission statement-performance hypothesis seems to be barely analyzed nor tested (Weiss and Piderit 1999). We addressed this issue by empirically examining the effectiveness of mission statements from an intra-organizational communication perspective and tested a theoretical rationale explaining the mission statement-performance hypothesis. The study results indicated that mission statements stimulate organizational members to engage in information conveyance and convergence processes, which prove to be positively related with the level of mission motivation. Higher levels of mission motivation, in turn, are assumed to be related with higher organizational performance.
Background Despite the omnipresence of mission statements, studies indicate that creating an effe... more Background Despite the omnipresence of mission statements, studies indicate that creating an effective mission statement is extremely difficult. Purposes Given the increasing pressure on health care administrators to develop an effective mission statement, this article sought to devise a state of the art of empirical mission statement research in order to develop a set of empirical based recommendations on how
Background: Although mission statements are one of the most popular management instruments, littl... more Background: Although mission statements are one of the most popular management instruments, little is known about the nature and direction of the presumed relationship between mission statements and organizational performance. In particular, empirical insights into the degree of mission statement use by individual organizational members are insufficient. Objectives We address the observed knowledge gap by (1) measuring the level of mission statement use (e.g., explaining the mission statement, making linkages to extant programs or practices, communicating enthusiasm, and adapting the mission statement to the personal work situation) by individual organizational members, and (2) identifying the antecedents that influence mission statement use. Design Questionnaires were used to collect data from a sample of 510 nurses from three Flemish hospitals. Mission statement use was measured by means of Fairhurst’s Management of Meaning Scale. Antecedents of mission statement use were derived ...
Van den Poel-www.crm.ugent.be Random Forests • Forest of decision trees • Introduced by Breiman (... more Van den Poel-www.crm.ugent.be Random Forests • Forest of decision trees • Introduced by Breiman (2001) to reduce instability of decision tree: " ... unstable learning algorithms-algorithms whose output classifier undergoes major changes in response to small changes in the training data. Decision-tree, neural network, and rule learning algorithms are all unstable." Dietterich (2000)
WIT Transactions on Information and Communication Technologies, Oct 14, 2003
In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various ... more In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various aspects of customer purchase behavior. However, to date, the applications of the technique have mainly focused on improving algorithms for detecting sequentially related events, whereas the implications of the sequences, and their incorporation into a global structure of consecutive sequences have been treated to a lesser extent. In this paper, such a structure, that we will refer to as sequential architecture, will be empirically investigated for a specific case in a fast moving consumer goods setting. Hence, the goal of this paper was to introduce a new concept that might prove to be a relevant tool for marketing decision making rather than offering a sound solution within a clearly demarcated problem definition. As opposed to the traditional sequence-analysis approaches, in this study, an array of binary Iogit analyses was applied for detecting significant sequences among category purchases. We use the output of the Iogit analyses to define the category that is most significantly influenced per newly purchased catego~, and we select these links for constructing the applicable sequential architecture. Finally, we provide empirical evidence that the methodology suggested is able to double the performance of predicting purchases in categories that were not purchased previously by the consumer, compared to a random model. In summary, we have shown that (i) binary logit analysis provides a feasible alternative for detecting and selecting highly significant sequential relationships, (ii) a sequential architecture can be successfully compiled through the methodology offered in this paper, and (iii) the provided sequential architecture can be a useful tool in understanding and predicting customer behavior. Future applications possibly lie ahead in the field of inter-category management, shelf-space allocation, store-layout decisions, retailer promotions, customer profiling and individual customer predictions.
International Conference on Data Mining, Sep 10, 2002
Response modeling is a very important application field of classification methods in direct marke... more Response modeling is a very important application field of classification methods in direct marketing because the success of a direct-mail campaign is highly dependent on who is being targeted. To date, standard classification models are applied to predict future purchasing behaviour for the complete customer file. In practice, however, companies use mailing budgets, i.e. only a subset of customers will be sent mail. Just those customers with sufficiently high-expected response rates are mailed to. The percentage of the total population that will actually receive the mailing is referred to as mailing depth. Hence, the real classification problem is not to classify all potential recipients as well as possible, but rather to find those customers, within the budget limitation, with the highest probability of response. Therefore, we propose an innovative alternative route to improved overall performance by tailoring the classification method to fit the problem at hand. We adapt binary logistic regression by iteratively changing the true values of the dependent variable during the maximum-likelihood estimation procedure. Those customers who rank lower than the cutoff in terms of predicted purchase probability, imposed by the mailing-depth restriction, will not contribute to the total likelihood. We illustrate our procedure on a real-life direct-marketing dataset comparing traditional response models to our innovative approach optimizing for a specific mailing depth. The results show that for mailing depths up to 48°/0 our method achieves significant and substantial profit increases.
Most analyses in marketing assume data to be either nominal or interval level. However, in many c... more Most analyses in marketing assume data to be either nominal or interval level. However, in many cases the data represent ordinal properties. Ranking data have been analysed in many disciplines using a wide range of methods, including distance-based models. Standard methods (eg ...
Here we introduce a web mining approach for automatically identifying new product ideas extracted... more Here we introduce a web mining approach for automatically identifying new product ideas extracted from web logs. A web log - also known as blog - is a web site that provides commentary, news, and further information on a subject written by individual persons. We can find a large amount of web logs for nearly each topic where consumers present their needs for new products. These new product ideas probably are valuable for producers as well as for researchers and developers. This is because they can lead to a new product development process. Finding these new product ideas is a well-known task in marketing. Therefore, with this automatic approach we support marketing activities by extracting new and useful product ideas from textual information in internet logs. This approach is implemented by a web-based application named Product Idea Web Log Miner where users from the marketing department provide descriptions of existing products. As a result, new product ideas are extracted from th...
Response modeling is a very important application field of classification methods in direct marke... more Response modeling is a very important application field of classification methods in direct marketing because the success of a direct-mail campaign is highly dependent on who is being targeted. To date, standard classification models are applied to predict future purchasing behaviour for the complete customer file. In practice, however, companies use mailing budgets, i.e. only a subset of customers will be sent mail. Just those customers with sufficiently high-expected response rates are mailed to. The percentage of the total population that will actually receive the mailing is referred to as mailing depth. Hence, the real classification problem is not to classify all potential recipients as well as possible, but rather to find those customers, within the budget limitation, with the highest probability of response. Therefore, we propose an innovative alternative route to improved overall performance by tailoring the classification method to fit the problem at hand. We adapt binary l...
This study focuses on the importance of mission valence and how public organisations can stimulat... more This study focuses on the importance of mission valence and how public organisations can stimulate a mission-oriented culture. More precisely, structural equation modelling was used to analyse a sample of 585 non-managerial employees employed by a public welfare organization with the aim of testing if (1) goal clarity, public service motivation and work impact are related with higher levels of mission valence, and (2) how communication with specific organizational sources influence these relationships. The study results indicate that goal clarity, public service motivation and work impact are positively related with mission valence.. In addition, the study results indicate that transformational leadership and co-workers influence perceptions of goal clarity, public service motivation and work impact. However, despite the fact that supervisors are often depicted as an interface between the individual and the organization, the study results indicate that supervisors influence goal cla...
In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various ... more In the marketing domain, sequential patterns have been usefi.dly deployed for predicting various aspects of customer purchase behavior. However, to date, the applications of the technique have mainly focused on improving algorithms for detecting sequentially related events, whereas the implications of the sequences, and their incorporation into a global structure of consecutive sequences have been treated to a lesser extent. In this paper, such a structure, that we will refer to as sequential architecture, will be empirically investigated for a specific case in a fast moving consumer goods setting. Hence, the goal of this paper was to introduce a new concept that might prove to be a relevant tool for marketing decision making rather than offering a sound solution within a clearly demarcated problem definition. As opposed to the traditional sequence-analysis approaches, in this study, an array of binary Iogit analyses was applied for detecting significant sequences among category purchases. We use the output of the Iogit analyses to define the category that is most significantly influenced per newly purchased catego~, and we select these links for constructing the applicable sequential architecture. Finally, we provide empirical evidence that the methodology suggested is able to double the performance of predicting purchases in categories that were not purchased previously by the consumer, compared to a random model. In summary, we have shown that (i) binary logit analysis provides a feasible alternative for detecting and selecting highly significant sequential relationships, (ii) a sequential architecture can be successfully compiled through the methodology offered in this paper, and (iii) the provided sequential architecture can be a useful tool in understanding and predicting customer behavior. Future applications possibly lie ahead in the field of inter-category management, shelf-space allocation, store-layout decisions, retailer promotions, customer profiling and individual customer predictions.
This study contributes to our understanding of how organizations can craft a mission-based cultur... more This study contributes to our understanding of how organizations can craft a mission-based culture by examining the relationship between mission valence, PSM, goal clarity and work impact. More specifically, the study assesses how value-laden communication with multiple intraorganizational socialization referents is related with the cited variables. The developed hypotheses are tested using structural equation modelling and a sample of 585 non-managerial employees employed by a public welfare organization. The findings confirm Wright et al.'s (2012) claim that position in an organizational hierarchy is not likely to influence the analyzed relationships. The magnitude of the relationships, however, diverges. In contrast to previous research, the study results indicate that, in the case of lower level employees, PSM is the most powerful predictor of mission valence. Furthermore, the results indicate that exposure to organizational values via interaction with internal socialization agents is positively related with their perceived importance. The results thus not only confirm the relevance of incorporating the institutional setting when analyzing mission valence but also provides further proof for an institutional theory of PSM by highlighting that different organizational socialization agents could play a distinctive role in crafting PSM and a mission-based culture.
Given the lack of insights into the micro-determinants of strategic planning (SP) in public organ... more Given the lack of insights into the micro-determinants of strategic planning (SP) in public organizations, this study uses information-processing theory and self-efficacy theory to investigate individual-level predictors of commitment to strategic plans among planning team members (PTMs). Specifically, we investigate whether plan commitment is contingent upon the fit between PTMs' preferred way of information-processing (i.e. their cognitive style) and the information-processing characteristics underlying SP processes in public organizations. Based on data gathered with 439 PTMs from 203 Flemish municipalities, we find that PTMs with a creating and planning style are committed to strategic plans because they deem SP useful.
Working Papers of Faculty of Economics and Business Administration Ghent University Belgium, 2009
Convinced that it will improve their performance, the majority of public and non-profit organizat... more Convinced that it will improve their performance, the majority of public and non-profit organizations has developed a formal mission statement. However, despite its popularity, the assumed mission statement-performance hypothesis seems to be barely analyzed nor tested (Weiss and Piderit 1999). We addressed this issue by empirically examining the effectiveness of mission statements from an intra-organizational communication perspective and tested a theoretical rationale explaining the mission statement-performance hypothesis. The study results indicated that mission statements stimulate organizational members to engage in information conveyance and convergence processes, which prove to be positively related with the level of mission motivation. Higher levels of mission motivation, in turn, are assumed to be related with higher organizational performance.
Background Despite the omnipresence of mission statements, studies indicate that creating an effe... more Background Despite the omnipresence of mission statements, studies indicate that creating an effective mission statement is extremely difficult. Purposes Given the increasing pressure on health care administrators to develop an effective mission statement, this article sought to devise a state of the art of empirical mission statement research in order to develop a set of empirical based recommendations on how
Background: Although mission statements are one of the most popular management instruments, littl... more Background: Although mission statements are one of the most popular management instruments, little is known about the nature and direction of the presumed relationship between mission statements and organizational performance. In particular, empirical insights into the degree of mission statement use by individual organizational members are insufficient. Objectives We address the observed knowledge gap by (1) measuring the level of mission statement use (e.g., explaining the mission statement, making linkages to extant programs or practices, communicating enthusiasm, and adapting the mission statement to the personal work situation) by individual organizational members, and (2) identifying the antecedents that influence mission statement use. Design Questionnaires were used to collect data from a sample of 510 nurses from three Flemish hospitals. Mission statement use was measured by means of Fairhurst’s Management of Meaning Scale. Antecedents of mission statement use were derived ...
Van den Poel-www.crm.ugent.be Random Forests • Forest of decision trees • Introduced by Breiman (... more Van den Poel-www.crm.ugent.be Random Forests • Forest of decision trees • Introduced by Breiman (2001) to reduce instability of decision tree: " ... unstable learning algorithms-algorithms whose output classifier undergoes major changes in response to small changes in the training data. Decision-tree, neural network, and rule learning algorithms are all unstable." Dietterich (2000)
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Papers by Anita Prinzie