<strong>Objectives:</strong> This study aimed to conduct a comparative assessment of bacterial cross-contamination in commercial and non-commercial processing plants including associated risk factors for b...<strong>Objectives:</strong> This study aimed to conduct a comparative assessment of bacterial cross-contamination in commercial and non-commercial processing plants including associated risk factors for bacterial contamination. <strong>Study Design</strong><strong>:</strong> This was analytic cross sectional survey on bacterial contamination of broiler carcasses between different processing systems. <strong>Introduction:</strong> Zambia, like most African and Asian Countries, still practices “live-open non-commercial broiler carcass processing systems” besides the “closed abattoir based systems”. However, shelf life, spoilage and hygiene levels have been postulated to vary based on the type of processing system. Live-open non-commercial processing systems are popular among majority consumers owing to their perceived “freshness”, compared to commercially dressed chickens. In between, consumers have to balance freshness and quality assurance. Ultimately, this becomes inert, remotely but an important public health issue. However, lack of empirical evidence on safety levels to guide consumer product selection leaves them to speculation. It is this need to close this gap that created an impetus for us to undertake this study. <strong>Methods:</strong> Biological samples were collected before carcass wash and after carcass wash alongside a structured questionnaire that gathered risk-associated data. Standard microbiological enumeration methods were used to isolate bacteria and enumerate contamination. <strong>Results:</strong> Broiler carcasses processed from “open” non-commercial systems were more contaminated (45.6%) than “closed-abattoir” commercially processed systems (35%). <em>Escherichia coli</em> were major contaminants (71.3%) and few <em>Salmonella</em> spices (typhi or para-typhi) in 1.3%. Risk analysis indicates washing (method) of carcasses at commercial systems was significantly more risky for contamination than non-commercial ones. Major sources of contamination were “distance from water sources”. Increased volume of slaughters per day (>15,000 birds) for commercial systems accounted for increased cross-contamination, particularly, distance from water source was a ma-jor risk factor for contamination.展开更多
The profit margin in the flour milling industry is quite narrow,so high-quality raw materials and efficiency of milling operations are crucial for every company. Many flour mills,especially those which import wheat fr...The profit margin in the flour milling industry is quite narrow,so high-quality raw materials and efficiency of milling operations are crucial for every company. Many flour mills,especially those which import wheat from other countries and have limited storage space for the different varieties or classes of wheat,can not afford to buy low quality wheat. Consequently,a mathematical model which can test the impact and interactions of raw materials,in technical point of view,would be a useful decision-making tool for the milling industry. A flour miller tests wheat for physical and chemical characteristics,cleanness and soundness. The miller also performs experimental milling,if available,to have some idea how the given wheat will behave during commercial milling. Based on these test results,the miller can only guess the commercial milling results such as flour yields and flour ash and protein contents. Thus,the objective of this study was to develop empirical equations to estimate commercial milling results,using the physical,chemical and experimental milling data of the given wheat blend and also,additionally,flour ash and protein specifications of the end-user. This was done by using the actual commercial milling procedures and their wheat physical,chemical,experimental milling data,and other vital data. Data were collected from a commercial mill located in East Asia that had four production lines and used wheat blend combinations from five different wheat classes,i.e. Hard Red Winter (HRW),Dark Northern Spring (DNS),Soft White (SW),Australian Soft (AS),and Australian Standard White (ASW) wheat to produce over 40 different products. The wheat physical and chemical characteristics included test weight,thousand kernel weight,ash and protein contents. The experimental milling data were straight-grade and patent flour yields,along with patent flour ash and protein contents from a Buhler experimental mill. The commercial milling results included the flour yields of patent,first clear,and second clear flours,as well as the ash and protein contents of commercial patent flours. Using multiple linear regression procedures,we have developed empirical equations to be able to estimate the commercial patent flour yields with R2 values above 0.90 for all four production lines,and commercial first clear flour yields with R2 values ranging 0.76 to 0.98,and the commercial patent flour protein contents with R2 values of 0.89 to 0.92. However,the yields of commercial second clear flours and the commercial patent flour ash contents were not able to be estimated with high coefficients of determination (R2 values). We recommend that the empirical equations for estimating commercial milling parameters should be derived using data from each individual flour milling company,for each production line of a given mill,and furthermore,tailored to specific products at a given ash and/or protein contents desired by end-users.展开更多
This paper presents a generic mathematical model for depicting the diffusion of an innovative product on a given market. Our approach relies on a probabilistic modeling of each customer behavior with respect to the co...This paper presents a generic mathematical model for depicting the diffusion of an innovative product on a given market. Our approach relies on a probabilistic modeling of each customer behavior with respect to the commercial process which is used to promote such a product. We introduce in particular the concept of coherent market that corresponds to a market which can be analyzed in a uniform way within our model. This last notion allows us to recover the classical empirical results that were discovered and widely studied by E.M. Rogers and his school. We explain finally how to use our approach as a support for analytic predictive marketing.展开更多
The challenges of disruptive innovations have gained significant attention from both academics and practitioners,commercialization being one of the most critical phases.At the same time,however,it is the less studied ...The challenges of disruptive innovations have gained significant attention from both academics and practitioners,commercialization being one of the most critical phases.At the same time,however,it is the less studied area of disruptive innovation.Therefore,this article examined scholarly papers on the commercialization of disruptive innovations through a multidisciplinary systematic literature review.It resulted in the analysis of 64 high-quality peer-reviewed academic articles.The analysis highlighted the commercialization models and main constructs that are affecting the commercialization process:market orientation,market learning,user’s involvement,market configuration,adoption networks and stakeholders,and innovation transference.The study evidences how commercialization has evolved from a later stage in innovation to influence even the early phases of innovation,characterized in turn by exploration,learning and ecosystem creation activities.Additionally,the analysis led to a proposition that established an integrated commercialization model for high uncertainty innovations.The model has three phases:1)Concept/value proposition validation,2)Business model validation&Market creation,and 3)Creating sales in the majority market.Lastly,the article contributes to a better understanding of commercialization processes in high uncertainty innovations,bridging also the academic-practitioner divide.展开更多
文摘<strong>Objectives:</strong> This study aimed to conduct a comparative assessment of bacterial cross-contamination in commercial and non-commercial processing plants including associated risk factors for bacterial contamination. <strong>Study Design</strong><strong>:</strong> This was analytic cross sectional survey on bacterial contamination of broiler carcasses between different processing systems. <strong>Introduction:</strong> Zambia, like most African and Asian Countries, still practices “live-open non-commercial broiler carcass processing systems” besides the “closed abattoir based systems”. However, shelf life, spoilage and hygiene levels have been postulated to vary based on the type of processing system. Live-open non-commercial processing systems are popular among majority consumers owing to their perceived “freshness”, compared to commercially dressed chickens. In between, consumers have to balance freshness and quality assurance. Ultimately, this becomes inert, remotely but an important public health issue. However, lack of empirical evidence on safety levels to guide consumer product selection leaves them to speculation. It is this need to close this gap that created an impetus for us to undertake this study. <strong>Methods:</strong> Biological samples were collected before carcass wash and after carcass wash alongside a structured questionnaire that gathered risk-associated data. Standard microbiological enumeration methods were used to isolate bacteria and enumerate contamination. <strong>Results:</strong> Broiler carcasses processed from “open” non-commercial systems were more contaminated (45.6%) than “closed-abattoir” commercially processed systems (35%). <em>Escherichia coli</em> were major contaminants (71.3%) and few <em>Salmonella</em> spices (typhi or para-typhi) in 1.3%. Risk analysis indicates washing (method) of carcasses at commercial systems was significantly more risky for contamination than non-commercial ones. Major sources of contamination were “distance from water sources”. Increased volume of slaughters per day (>15,000 birds) for commercial systems accounted for increased cross-contamination, particularly, distance from water source was a ma-jor risk factor for contamination.
文摘The profit margin in the flour milling industry is quite narrow,so high-quality raw materials and efficiency of milling operations are crucial for every company. Many flour mills,especially those which import wheat from other countries and have limited storage space for the different varieties or classes of wheat,can not afford to buy low quality wheat. Consequently,a mathematical model which can test the impact and interactions of raw materials,in technical point of view,would be a useful decision-making tool for the milling industry. A flour miller tests wheat for physical and chemical characteristics,cleanness and soundness. The miller also performs experimental milling,if available,to have some idea how the given wheat will behave during commercial milling. Based on these test results,the miller can only guess the commercial milling results such as flour yields and flour ash and protein contents. Thus,the objective of this study was to develop empirical equations to estimate commercial milling results,using the physical,chemical and experimental milling data of the given wheat blend and also,additionally,flour ash and protein specifications of the end-user. This was done by using the actual commercial milling procedures and their wheat physical,chemical,experimental milling data,and other vital data. Data were collected from a commercial mill located in East Asia that had four production lines and used wheat blend combinations from five different wheat classes,i.e. Hard Red Winter (HRW),Dark Northern Spring (DNS),Soft White (SW),Australian Soft (AS),and Australian Standard White (ASW) wheat to produce over 40 different products. The wheat physical and chemical characteristics included test weight,thousand kernel weight,ash and protein contents. The experimental milling data were straight-grade and patent flour yields,along with patent flour ash and protein contents from a Buhler experimental mill. The commercial milling results included the flour yields of patent,first clear,and second clear flours,as well as the ash and protein contents of commercial patent flours. Using multiple linear regression procedures,we have developed empirical equations to be able to estimate the commercial patent flour yields with R2 values above 0.90 for all four production lines,and commercial first clear flour yields with R2 values ranging 0.76 to 0.98,and the commercial patent flour protein contents with R2 values of 0.89 to 0.92. However,the yields of commercial second clear flours and the commercial patent flour ash contents were not able to be estimated with high coefficients of determination (R2 values). We recommend that the empirical equations for estimating commercial milling parameters should be derived using data from each individual flour milling company,for each production line of a given mill,and furthermore,tailored to specific products at a given ash and/or protein contents desired by end-users.
基金This paper was supported by the Ecole Polytechnique and Thales chair "Engineering of Complex Systems".
文摘This paper presents a generic mathematical model for depicting the diffusion of an innovative product on a given market. Our approach relies on a probabilistic modeling of each customer behavior with respect to the commercial process which is used to promote such a product. We introduce in particular the concept of coherent market that corresponds to a market which can be analyzed in a uniform way within our model. This last notion allows us to recover the classical empirical results that were discovered and widely studied by E.M. Rogers and his school. We explain finally how to use our approach as a support for analytic predictive marketing.
文摘The challenges of disruptive innovations have gained significant attention from both academics and practitioners,commercialization being one of the most critical phases.At the same time,however,it is the less studied area of disruptive innovation.Therefore,this article examined scholarly papers on the commercialization of disruptive innovations through a multidisciplinary systematic literature review.It resulted in the analysis of 64 high-quality peer-reviewed academic articles.The analysis highlighted the commercialization models and main constructs that are affecting the commercialization process:market orientation,market learning,user’s involvement,market configuration,adoption networks and stakeholders,and innovation transference.The study evidences how commercialization has evolved from a later stage in innovation to influence even the early phases of innovation,characterized in turn by exploration,learning and ecosystem creation activities.Additionally,the analysis led to a proposition that established an integrated commercialization model for high uncertainty innovations.The model has three phases:1)Concept/value proposition validation,2)Business model validation&Market creation,and 3)Creating sales in the majority market.Lastly,the article contributes to a better understanding of commercialization processes in high uncertainty innovations,bridging also the academic-practitioner divide.