A techno-managerial approach in food quality management research

Trends in Food Science & Technology 17 (2006) 378–385

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A techno-managerial approach in food quality management research Pieternel A. Luninga,* and Willem J. Marcelisb

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a

Product Design and Quality Management Group, Department of Agrotechnology and Food Sciences, Wageningen University, P.O. Box 8129, NL-6700 EV Wageningen, The Netherlands (Address: Product Design and Quality Management Group, Wageningen University and Research Centre, Building 307, Bomenweg 2, 6703 HD Wageningen, Gelderland, The Netherlands. Tel.: C31 317 482087; fax: C31 317 483669; e-mail: [email protected]) b

Management Studies Group, Department of Social Sciences, Wageningen University, P.O. Box 8130, 6700 EW Wageningen, The Netherlands

In this article it is discussed that food quality management issues are much more complex than often assumed and that it requires a specific research approach. It is argued that food quality management deals with dynamic and complex food systems and people systems involved in realising food quality. A conceptual food quality relationship is developed, assuming that food quality is a function of both food and human behaviour and their interaction. The relationship reflects that food quality is dependent on both dynamic properties of the food product, as related to applied technological conditions, and dynamic properties of people, as related to applied administrative conditions. A technomanagerial approach to research food quality management issues is derived, which involves the integrated analysis of theories from technological and managerial sciences.

* Corresponding author. 0924-2244/$ - see front matter q 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.tifs.2006.01.012

Introduction The result of agribusiness and food industry, as the combined action of individuals in the whole agri-food production chain striving for food quality, is much more uncertain than often is assumed (Luning, Marcelis, & Jongen, 2002; Van der Spiegel, 2004; Van der Spiegel, Luning, Ziggers, & Jongen, 2003, 2005). This is clearly illustrated by the various serious affairs that occurred in food chains in West Europe in the last decade. Examples are bovine spongiform encephalopathy (BSE) and classical swine fever (CSF) in 1997, the Belgian dioxin affair in (1999) and dioxin in potato skins for animal feed (in 2004), foot and mouth disease (FMD) in 2001, the nitrophen and medroxyprogesteron acetate (MPA) incidents in 2002, and Avian Influenza in 2003 and 2005 (Agriholland, 2003; Crawford, 1999; Food Alert notification, 2004; LNV, 1997, 2001; USDA, 2001). The dioxin crisis in 1999 in Belgium is very illustrative for the uncertainty in production of safe and high quality food. The origin of this crisis was traced back to the production of ingredients for animal feed. Motor oil was mixed deliberately or accidentally (still unknown) with frying fat that was aimed for production of ingredients for animal feed. The dioxin contamination entered the food chain via animal feed and ultimately resulted in a serious crisis for agribusiness and food industry. The first signal occurred in the beginning of the year, when chickens got ill. However, it took up to July before the origin of the dioxin contamination was traced back. Very heavy measures had to be taken to regain consumer trust, because there was much uncertainty about the contamination route of dioxin, but also due to the full media attention in combination with confusing reports of officials. Ultimate costs were estimated on 1.54 billions US dollars for both the agricultural and food sector (Belgian dioxin crisis, 1999). This example illustrates that peoples’ decision-making behaviour in combination with the technological complexity can have unexpected dramatic consequences on food safety and quality due to, amongst others, lack of knowledge of the origin and mechanism of the hazard, lack of information and improper communication. In this paper, the mechanisms that may contribute to the complexity of food quality management are analysed and discussed. Subsequently, we propose and discuss a techno-managerial research approach to analyse food

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quality management issues in order to deal with this complexity. Complex systems in food quality management Food quality management deals with both food quality and quality management. It therefore concerns both the food production systems and the people systems, which are involved in realising food quality. To obtain a better understanding of why these systems can be considered as complex we use the systems hierarchy theory of Boulding (1956) to characterise the different system levels involved in food quality management. The hierarchy of Boulding (1956) provided fundamental insights in systems thinking. He distinguished nine system levels. Each higher level includes all lower levels but new functions are added and more information is needed. The levels are shortly described below: 1 Frame-work system: a static structure, e.g. a stone. These systems are also described as skeleton systems. 2 Clock-work system: a system with predetermined motion, e.g. a clock. The factor time has been added, resulting in simple dynamic systems. 3 Cybernetic system: closed-loop control system, e.g. a thermostat. At this level through feedback information one or more variables are kept at a constant level. 4 Open system: structurally self-maintaining, self-production, e.g. biological cells. Here life starts with selfmaintaining and self-reproduction. At this level total information is passed through the living system. 5 Lower organism system: differentiation in organs, predetermined growth, reproduction, e.g. plants. At this level the systems are able to group cells to organs with predetermined final forms and functions. 6 Animal system: consciousness, information collection, brains guiding behaviour, i.e. animals. The animal system adds to the plant system the ability to process and store information. Special organs for information retrieval are formed (ear, eye). Consciousness arises in the form of images, knowledge structure and an overview over the environment as a whole. 7 Human system: self-reflection, knowledge, anticipation, and symbolic language, i.e. human beings. At this level self-reflection is added. Human beings not only know, but they know that they know. This ability is connected with the ability to form a language and to symbolise. Human beings are also aware of time and are thus able to anticipate. 8 Social system: relationships, interests, communication, culture, e.g. an organisation. Humans are only human in a social situation, where he/she plays different roles. The social organisation has its own variables, like values, norms, goals, social relationships and different interests. Culture arises within social organisations. 9 Transcendental system: non-material systems, e.g. the idea of divinity. At the end there are non-material

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systems of logic, axioms and belief, including questions without information to answer them. According to Boulding (1956), increasing system levels correspond with a higher level of complexity. As a consequence, these higher system levels do have a more unpredictable behaviour. From the viewpoint of this hierarchy, food systems belong to the levels 4–6, which are living systems. So, these systems are rather complex, compared to product systems without living materials. People involved in quality management and the social system where they are in, are classified in the higher levels 7–8. Realising that food and human systems belong to the higher system levels, an interesting problem is coming up. People often perceive it as too difficult to understand and analyse complex systems, and to predict their behaviour in time. When people are confronted with ambiguity, they try to ignore it or make sense of it in ways that reflect their own perception of the situation rather than the situation itself (Teale, Dispenza, Flynn, & Currie, 2003).Therefore, complex problems are commonly reduced to a lower system level, which enables a straightforward choice of solutions. Likewise, despite its complexity, food quality management is often assumed to be a rather controllable process on the cybernetic system level (Luning et al., 2002). Consequently, straightforward mechanisms of control are introduced to manage the variation in outcome, which is illustrated by the great attention that is paid to the development and implementation of quality systems in agribusiness and food industry (e.g. Efstratiadis, Karirti, & Arvanitoyannis, 2000; Ropkins & Beck, 2000). These quality systems are commonly based on procedures and control circles as mechanism to control and assure quality. After implementation, however, it often appears in practice that the intended results are not obtained, without full understanding of the reasons, which is illustrated in Section 3.

Problems with quality systems Literature on management of food quality is mainly focused on development, application and integration of quality systems. Much attention is paid to the performance of HACCP, and screening literature revealed typical observations, such as: † Problems related with the food production systems like, difficulties with identifying and prioritising chemical/ microbial hazards, and assessing critical points on a scientific and quantitative basis due to, e.g. to lack of scientific data, different approaches, and or variation in (microbial) standards resulting in different assessments on safety (Holt & Henson, 2000; Ropkins & Beck, 2000, 2003; Todd, 2003; Untermann, 1999).

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† Problems related to technological measuring and equipment such as, no relevant monitoring systems (Mitchell, 1998), use of wrong equipment (Walker, Pritchard, & Forsythe, 2003), lack of equipment, incorrect plant lay out, and poorly designed equipment (Panisello & Quantick, 2001). † Problems due to improper food handler behaviour like inappropriate corrective actions (Legnani, Leoni, Berveglieri, Mirolo, & Alvaro, 2004; Motarjemi & Ka¨ferstein, 1999), and insufficient record-keeping and documentation (Motarjemi & Ka¨ferstein, 1999; Vela & Fernande´z, 2003; Walker et al., 2003). † Typical factors contributing to improper behaviour involve lack of understanding the HACCP system (Motarjemi & Ka¨ferstein, 1999; Taylor & Kane, in press), ineffective training (Howes, McEwen, Griffiths, & Harris, 1996), misperceptions on safety risks (Clayton, Griffith, Price, & Peters, 2002), no commitment of management (often reflected in insufficient support in time, money, training of employees, motivation) (Vela & Fernande´z, 2003), psychological barriers to HACCP implementation (like, HACCP is perceived as difficult, burdensome, unnecessary and hindered by staff and external problems) (Taylor & Taylor, 2004), and lack of validation and verification of the HACCP system (Taylor & Kane, in press). Above findings show problems originating from food systems (like, complexity and variation of food products and processes) and problems related to people (such as, differing quality perceptions, poor commitment, or inappropriate supporting conditions). We conclude from these findings that dealing with food quality management as a cybernetic system, relying on control mechanisms, seems to deny all kinds of influencing factors that can not be predicted with such an approach. Consider, for example, unpredictable behaviour of raw materials, and conflicting individual interests of people resulting in other behaviour than expected (e.g. Gerats, 1990; Luning et al., 2002; Van der Spiegel, 2004).

Characterising food quality management Therefore, from a research point of view we need a more sophisticated approach to prevent simplification of food and human systems to cybernetic systems, and to explicitly consider their real complexity to better predict their behaviour and from that the outcome of these systems. In this section, we typify the systems and subsequently characterise food quality management. Typifying systems A food system is described here as the whole of product properties (ranging from raw materials, ingredients to final products) and profiles of reaction processes

(i.e. microbial, chemical, biochemical, physical and physiological food processes). Food behaviour is the result of the outcomes of the food system over time. A food system is subject to a food production system, which is described as the whole of production activities and technological conditions influencing reaction processes in order to realise desired product properties. These properties are perceived as quality attributes depending on expectations and experiences of customers and consumers (Van Trijp & Steenkamp, 2004). Food and food production systems are typically living materials with large variation, which change over time. Variability of these systems can be ascribed to: † heterogeneity of food products (e.g. constituents not homogenously distributed or locked in compartments) (e.g. Pomeranz & Meloan, 1994). † large compositional variations due to cultivar/breeding differences, seasonal influences, weather and harvesting conditions (e.g. Tijskens, Konopacki, Simcic, & Hribar, 2000). † continuous decay of quality attributes due to a wide range food processes each has its own behaviour depending on applied processes (e.g. Van Boekel, 1998). † interactions between food compounds (e.g. Hidalgo & Zamora, 2004) and with packaging (e.g. Helmroth, Rijk, Dekker, & Jongen, 2002) and equipment materials (e.g. Wolf, 2004). So, food can be considered as a complex system with a dynamic and variable behaviour, it changes in time and changes may differ for similar food products. For example, levels of glucosinolates in processed Brassica vegetables upon consumption can vary a 100-fold, due to a variation of 5–10 in raw materials, a 5–10-fold variation caused by industrial processing and storage and a 5–10-fold variation by household preparation (Dekker, Verkerk, & Jongen, 2000). Human systems are perceived here as people with certain individual characteristics making decisions in order to reach goals. Human behaviour is then described as the decisionmaking outcomes of the human system over time. Simon (1960) recognised that people do not always make decisions with logic and rationality and introduced two concepts in his administrative model, i.e. bounded rationality (i.e. incomplete information, limited knowledge) and satisfying behaviour (i.e. choosing first satisfactory alternative). According to this approach, one is accepting that people have their own way of dealing with problems, being more or less subjective therein. As a consequence human behaviour is rather unpredictable. Human systems are subject to a management system, which is described as a whole of managerial activities and administrative conditions (e.g. organisational relationships, available information) influencing decision-making

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activities. The resulting decisions are meant to initiate actions towards people and towards the food production system in order to manage them to realise food quality. Characterising decision-making of people reveals that it is a complex and dynamic process. Decision-making can be influenced by various aspects like type of information (Holbrook & Moore, 1981; Paivio, 1991) personal characteristics (Forgas & George, 2001; Seagal & Horne, 1997; Shepherd, 1985), motivation and ability (Gerats, 1990; Petty & Cacioppo, 1981, 1986; Wood, 2000) but also organisational conditions, conflicting interests, availability of information and power (Forgas & George, 2001; Jacoby, Johar, & Morrin, 1998; Kampfraath & Marcelis, 1981; Mintzberg, 1983; 1993). Besides the complex and dynamic character of decision-making of people, also organisational conditions do have their own dynamics and life cycle, due to a continuous changing environment that requires organisations to adapt (Robbins, 2000). Therefore, under various organisational conditions, decision-making will result in different outcomes. Considering above-mentioned aspects of food and human systems, our conclusion is that food quality management research should start with understanding behaviour of food and human systems when trying to predict the outcome of these systems in terms of quality.

Characterising food quality management Teale et al. (2003) mentioned that in managerial decision-making it is not uncommon to see a clockwork universe and to be convinced that behaviour can be predicted towards a predetermined end. They discussed that, in analysing management problems, chaos theory may contribute to a better understanding of behaviour, starting with the consideration that systems are apparently disordered. Within this perspective chaos theory is concerned with ambiguity and uncertainty. Ambiguity is

9. Transcendental 8. Social 7. Human 6. Animal

described as a situation where there is no clear interpretation of phenomena or events; available evidence supports more than one interpretation. Uncertainty is the situation where there is lack of information about phenomena or events. Chaos theory implies that everything is in essence chaotic, but the way a certain situation develops will follow a certain law of nature (Teale et al., 2003). In Fig. 1 we propose a schematic representation of ambiguity and uncertainty, where we consider higher systems as more chaotic. We assume that systems at higher levels are causing more ambiguity due to lack of understanding of underlying factors and mechanisms. Uncertainty is assumed to be only dependent on lack of availability of information. Fig. 1 shows that in the situation of order, low ambiguity and uncertainty exist due to fully understood systems being fully informed about them. A situation of order can be characterised by aspects like: linearity, rationality and stability. More chaos will result in more ambiguity and uncertainty. The ultimate situation of chaos is one of non-linearity, irrationality and instability. From above perspective we conclude that food quality management research and analysis should assume a situation of relative chaos and not order, and recognise ambiguity and uncertainty. As mentioned above, both food and human systems do have their own dynamic behaviour, and therefore they are not fully predictable. However, conditioning will generate organised and patterned behaviour (Kampfraath & Marcelis, 1981; Teale et al., 2003). Conditioning is aimed at reducing variation in dynamic behaviour and it creates boundaries to constrain extremes in behaviour outcomes. Accordingly, the dynamics of food properties (e.g. variable content of vitamins) can be influenced and controlled by applying technological conditions (e.g. breeding circumstances and or time-temperature

Ambiguity

due to lack of understanding

Chaos

5. Plant 4. Cell 3. Cybernetic 2. Clock-work Order

1. Frame-work

System level

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Uncertainty due to lack of information

Fig. 1. Managerial complexity, dependent on ambiguity and uncertainty.

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processing conditions), which enables a better prediction of food behaviour. Similarly, the dynamics of people (e.g. different decisions) can be directed to a certain extent by applying administrative conditions (e.g. providing information or training), which enables a better prediction of people behaviour (Kampfraath & Marcelis, 1981; Robbins, 2000). Although variation in food and human behaviour can be conditioned to a certain extent, enabling a certain level of prediction and control, it should be recognised that due to its complexity it is not possible to fully predict the food quality outcome. Even products in a properly maintained production line with adequately trained and motivated workers, the right raw materials, expert supervisors, and quality control employees who know what they are doing, cannot be perfectly uniform, without defects and variation (Hubbard, 1996). We conclude that analysis of behaviour of food and human systems should be based on both system dynamics and conditions to better predict the quality outcome. Food quality relationship model Based on the conclusions above, we hypothesise that the realisation of food quality is dependent on both food and human behaviour, as reflected in the relationship below: Food qualityZf (food behaviour, human behaviour), whereby Food behaviourZf (food dynamics, technological conditions), and Human behaviourZf (human dynamics, administrative conditions)

In this relationship we assume that food quality is dependent on both dynamic properties of the food product as related to applied technological conditions and dynamic properties of people as related to applied administrative conditions and that both systems might affect each other.

Managerial approach

Technological facts

More specifically, food dynamics refers to variability of its properties. It involves variation in composition of food products (including raw materials, ingredients, manufactured or fresh produce) like content of sugars, flavour concentration, initial contamination of bacteria, and variation in behaviour profiles of product inherent microbial, chemical, physical, physiological and biochemical processes. Examples of these processes are growth or inactivation of pathogens, enzymatic reactions, moisture diffusion, or respiration of fruits; these processes change food properties and related quality attributes (e.g. colour, taste, safety, etc.) in time. Technological conditions are measures to influence and control compositional variation and dynamics of the wide range of food processes. Examples of these conditions involve, harvesting and handling circumstances, hygienic design situation, processing conditions (e.g. time temperature, pressure, etc.) packaging concepts or storage conditions. The separate effects on quality of food properties and processes as related to technological conditions are mainly understood but not effects of their interactions on quality. Human dynamics refers to variability of decisionmaking behaviour related to food quality management issues. Crucial steps in decision-making involve formation of perception, attitude, and choice intention, respectively, and actual decision-making (e.g. Jacoby et al., 1998; Mintzberg, Raisinghani, & Theoret, 1976). These decision-making steps are influenced by various factors like, information, personal characteristics and social/organisational circumstances. These factors contribute to variation in decision outcomes (Robbins, 2000). Administrative conditions are measures that are taken to direct people behaviour in a certain way. Typical examples of administrative conditions are organisational structure, working conditions (ranging from physical

Techno-managerial approach

Technological aspects

Techno-

Managerial approach

Technological approach

Technological approach

managerial approach Management aspects

Management facts

Fig. 2. Schematic presentation of a techno-managerial approach.

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facilities to team structures), procedures, management techniques (e.g. quality function deployment) or communication systems.

Techno-managerial research approach From above we conclude that, to predict food quality one should analyse food and human behaviour. We therefore advocate a techno-managerial (TM) research approach, which includes the integrative use of technological and managerial theories, wherein technological theories are explaining food behaviour and managerial theories are explaining human behaviour, and integrative use refers to integrating these theories due to the mutual influence of food and human behaviour on each other. Fig. 2 illustrates how a techno-managerial research approach differs from a managerial or a technological one. Typical for a managerial approach is that technological aspects are considered as given facts, whereas in a technological approach, management aspects are considered as not changeable boundary restrictions (Luning et al., 2002). We define the technomanagerial approach in the analysis and research of food quality management as: the integrative use of technological and managerial theories, in order to explain and predict food quality from food and human behaviour. The techno-managerial approach is illustrated with a research example. This example deals with a meat company, covering the whole production chain. The company was confronted with problems with Salmonella in pig meat. Since Salmonella infection attains increasing attention from both consumers and government, it is expected that, legal requirements on salmonella-free production and delivery in the pig meat chain need to be implemented in the near future. In anticipation to these requirements, top management wanted to know what would be an appropriate quality system to deal with the risk of salmonella infection. From a technological perspective, amongst others, two relevant models were selected to analyse the research issue. The first one was a general model indicating which technological factors influence food quality at each link in the food chain (like breed choice, animal feeding and housing, transport conditions of animals, hygienic conditions in slaughterhouses and store rooms, food processing parameters, packaging properties, and distribution and storage facilities at retail and consumer’s place) (Luning et al., 2002). The second, more specific model from Berends (1998), distinguishes three groups of factors determining Salmonella infection including (1) pig-related factors, like age, health, immunity and stress, (2) agens-related factors, like virulent factors and serotype specific plasmides, and (3) external factors, like antibiotics, feed and hygiene. Analysis of the research issue with these technological

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models resulted in several solutions that had one characteristic in common: technological measures. Typical options for solutions were new medication, salmonella-free feed, building new receipt rooms in the slaughterhouse, a higher cleaning frequency in the slaughterhouse, and new packaging materials. From a managerial perspective three relevant models were identified. One model on quality behaviour, validated for slaughterhouse situations, indicates that actual decisionmaking behaviour on quality issues is dependent on disposition and ability to quality. Whereby disposition to quality is influenced by factors such as personal quality standard, quality knowledge and observed standards of colleagues, and ability to quality includes factors such as skills and competences, availability of time and support of supervisors (Gerats, 1990). The second model distinguishes five specific food quality management functions, respectively, quality design, control, improvement, assurance, and quality policy and strategy (Luning et al., 2002). The last model revealed four critical factors for success in pig meat chains, i.e. involvement of all partners in the chain, mutual trust, right division of costs and returns, and open information exchange (Brink et al., 1997). Analysis of the research issue with these managerial models resulted in several solutions that had one characteristic in common: managerial measures. Typical options for solutions included meetings between chain partners, training of workers and supervisors, implementing an information system, developing chain quality assurance procedures and organising quality circles. In addition to the importance of using different disciplines, we propose that technological and managerial models should be connected, in order to analyse how food and human behaviour affect each other. Although in the example of salmonella contamination in the pig meat chain, both technological (T) and managerial (M) models seem to be applicable and relevant, the effects of changing food and human behaviour on each other has to be judged, because food behaviour is assumed to be dependent, at least partially, on human behaviour and vice versa. For instance, the effect of new medication (T) will be dependent on having a control system and appropriate specific quality knowledge of people involved (M). The effect of Salmonella-free feed (T) will depend on how the feed is used at a farm, so the farm’s control system and information exchange with the feed supplier will play a role (M). Building new receipt rooms (T) will be effective only when slaughterhouses organise an incoming pig control system (M). The effect of a higher cleaning frequency in the slaughterhouse (T) will merely be applicable when time is really available and quality skills and competencies are sufficient (M). As last example, the effect of new packaging materials (T) depends on stores and consumers knowing how to handle packed pig meat (M). On the other hand the effect of managerial measures will be dependent on technological influences. In this case

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meetings between chain partners (M) will be successful when they really are influencing each other, due to a technological dependency (T). Training of workers and supervisors (M) will be effective only when the technological process really enables them to influence product quality (T) in their daily work situation. An information system is meant to support decisions for action towards the production process (M), but depends on being able to technologically vary the product and or process (T). Quality assurance procedures (M) do have more effect when it supports predictability and controllability of the process (T). Finally, quality circles (M) will fail when product and or process mechanisms are too complex to clearly understand (T). By systematically analysing in this way, the joint effects of technological and managerial measures can be taken into account. We assume that the effects on final quality of technological measures can be better predicted when looking to related human behaviour, and vice versa. In practice, various orientations are used for analysing food quality management issues, depending on organisation’s culture and individual beliefs of managers and researchers. In situations where technology plays an important role, often technological solutions are preferred in order to make product quality and production processes controllable, such as automation of processes and redesign of products and processes. In other situations, managers and researchers prefer changing culture and attitude of employees, because they strongly belief that this is the only way to accomplish improvements. As a consequence, quality issues are analysed according to characteristics of people and the organisation. Solutions are searched in changing people’s attitude and knowledge by means of training and changing culture, and in describing responsibilities, procedures and work instructions (Luning et al., 2002). These orientations reflect people’s priorities, which have been developed due to their different education and experience (Brocklesby, 1997; Mingers, 1997). From a methodological viewpoint, Mingers (1997) advocated that using theories from different paradigms is necessary to deal effectively with real world situations, which are highly complex and multidimensional. Adopting only one paradigm (e.g. only technological or managerial) is inevitably gaining only a limited view of a particular problem situation. Combining different methodologies is expected to yield a better result than a single focus (Mingers, 1997).

Conclusion The complexity of food quality management tells us that analysis and research should start with assuming uncertainty and ambiguity. Our techno-managerial research approach requires increase of information (to reduce uncertainty) and enlargement of knowledge on underlying factors and mechanisms (to reduce ambiguity) of both food and human systems to enable a more accurate level of prediction.

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