Demand management research has always attracted considerable attention from academia and industry, covering almost all fields, including multiple disciplines, including philosophy, economics, mathematics, management, psychology, etc. This paper provides a systematic review of 110 peer-reviewed journal articles published from 2013 to 2018. The primary purpose is to study how companies design and plan optimal product sales decisions under different demand patterns. We passed to organize and analyze these 110 articles, summarizing the specific role of demand on the consumer goods supply chain, and the relationship to corporate sales decisions. We found that customer demand has driving force and starting point for suppliers to make product sales decisions in the field of consumer goods supply chain. The customer demand for products dramatically affects the degree of market segmentation and also determines the benefits of manufacturers and retailers. However, the existing research is only done under the uncertainty of demand and does not consider the three different demand patterns, real, false, and semi-real. Therefore, there is a significant theoretical gap in existing research. Our goal is to establish a theoretical bridge through the combing and review of relevant literature systems and to construct a conceptual model of the demand-oriented supply chain. This conceptual model will provide an essential reference for the direction of future research.
| Published in | Mathematics and Computer Science (Volume 4, Issue 2) |
| DOI | 10.11648/j.mcs.20190402.11 |
| Page(s) | 41-56 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Demand Orientation, Supply Chain, Precision Marketing, Sales Decision
| [1] | Gause, D. C., & Weinberg, G. M. (2011). Exploring requirements: quality before design. New York: Dorset House Pub. |
| [2] | Zhang, B., Duan, D., & Ma, Y. (2018). Multi-product expedited ordering with demand forecast updates. International Journal of Production Economics, (206): 196-208. |
| [3] | Chong, A. Y. L., Ch’ng, E., Liu, M. J., & Li, B. (2015). Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews. International Journal of Production Research, 55 (17): 5142-5156. |
| [4] | Li, L., Chi, T., Hao, T., & Yu, T. (2018). Customer demand analysis of the electronic commerce supply chain using Big Data. Annals of Operations Research, 268 (1-2): 113-128. |
| [5] | Engler, T. H., Winter, P., & Schulz, M. (2015). Understanding online product ratings: A customer satisfaction model. Journal of Retailing and Consumer Services, (27): 113-120. |
| [6] | Schweigert, W. A. (2012). Research Methods in Psychology (3rd Revised ed.). Long Grove, IL: Waveland. |
| [7] | Mintzberg, H. (1979). An Emerging Strategy of “Direct” Research. Administrative Science Quarterly, 24 (4): 582-589. |
| [8] | Boyles, D. R. (2006). Dewey's Epistemology: An argument for warranted assertions, knowing, and meaningful classroom practice. Educational Theory, 56 (1): 57-68. |
| [9] | Robert I. Sutton & Barry M. Staw. (1995). What Theory is Not. Administrative Science Quarterly, 40 (3): 371-384. |
| [10] | Mackenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in mis and behavioral research: integrating new and existing techniques. MIS Quarterly, 35 (2): 293-334. |
| [11] | Kotler, P., Saliba, S., & Wrenn, B. (1991). Marketing management: Analysis, planning, and control: Instructor's Manual. Prentice-hall. |
| [12] | Shinichi Nogami. (2018). Marketing Yogo Zukan. Tokyo: Shinsei Publishing Co. Ltd. |
| [13] | Marcuse, H. (1991). One-dimensional man: Studies in the ideology of advanced industrial society (2nd edition). Gibraltar: Beacon Press. |
| [14] | Miller, D. (1987). Material Culture and Mass Consumption, Oxford: Basil Blackwell Ltd. |
| [15] | Crawford, M. (2004). The world in a shopping mall. In variations on a theme park: The new American city and the end of public space, ed. Sorkin. M. pp. 3-30. New York: Hill & Wang. |
| [16] | Li, C., & Lim, A. (2018). A greedy aggregation–decomposition method for intermittent demand forecasting in fashion retailing. European Journal of Operational Research, 269 (3): 860-869. |
| [17] | Mawdsley, J. K., & Somaya, D. (2018). Demand-side strategy, relational advantage, and partner-driven corporate scope: The case for client-led diversification. Strategic Management Journal, 39 (7): 1834-1859. |
| [18] | Elhafsi, M., & Hamouda, E. (2018). Managing an integrated production and inventory system selling to a dual market: Long-term and walk-in. European Journal of Operational Research, 268 (1): 215-230. |
| [19] | Hildebrand, C., Häubl, G., Herrmann, A., & Landwehr, J. R. (2013). When social media can be bad for you: Community feedback stifles consumer creativity and reduces satisfaction with self-designed products. Information Systems Research, 24 (1): 14-29. |
| [20] | Duarte, P., e Silva, S. C., & Ferreira, M. B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM. Journal of Retailing and Consumer Services, (44): 161-169. |
| [21] | Fargnoli, M., Costantino, F., Di Gravio, G., & Tronci, M. (2018). Product service-systems implementation: A customized framework to enhance sustainability and customer satisfaction. Journal of Cleaner Production, (188): 387-401. |
| [22] | Yuan, H., Gómez, M. I., & Rao, V. R. (2013). Trade promotion decisions under demand uncertainty: A market experiment approach. Management Science, 59 (7): 1709-1724. |
| [23] | Bell, D. R., Gallino, S., & Moreno, A. (2018). Offline showrooms in omnichannel retail: Demand and operational benefits. Management Science, 64 (4): 1629-1651. |
| [24] | Xu, X., Munson, C. L., & Zeng, S. (2017). The impact of e-service offerings on the demand of online customers. International Journal of Production Economics, (184): 231-244. |
| [25] | See-To, E. W., & Ngai, E. W. (2018). Customer reviews for demand distribution and sales nowcasting: a big data approach. Annals of Operations Research, 270 (1-2): 415-431. |
| [26] | Aguwa, C. C., Monplaisir, L., & Turgut, O. (2012). Voice of the customer: Customer satisfaction ratio based analysis. Expert Systems with Applications, 39 (11): 10112-10119. |
| [27] | Kwon, K., & Kim, C. (2012). How to design personalization in a context of customer retention: Who personalizes what and to what extent?. Electronic Commerce Research and Applications, 11 (2): 101-116. |
| [28] | Tseng, M. M., Jiao, R. J., & Wang, C. (2010). Design for mass personalization. CIRP annals, 59 (1): 175-178. |
| [29] | Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British journal of management, 14 (3), 207-222. |
| [30] | Sandberg, J., & Tsoukas, H. (2011). Grasping the logic of practice: Theorizing through practical rationality. Academy of management review, 36 (2), 338-360. |
| [31] | Richard, J., Light, R., & Pillemer, D. B. (1984). Summing up. Cambridge, MA: Harvard University Press. |
| [32] | Ordanini, A., Rubera, G., & DeFillippi, R. (2008). The many moods of inter‐organizational imitation: A critical review. International Journal of Management Reviews, 10 (4), 375-398. |
| [33] | Calabrò, A., Vecchiarini, M., Gast, J., Campopiano, G., De Massis, A., & Kraus, S. (2018). Innovation in family firms: a systematic literature review and guidance for future research. International Journal of Management Reviews. In Press. |
| [34] | Merton, R. K., & Merton, R. C. (1968). Social theory and social structure. Simon and Schuster. |
| [35] | Kemp-Benedict, E. (2013). Material needs and aggregate demand. The Journal of Socio-Economics, (44): 16-26. |
| [36] | Torriti, J. (2014). A review of time use models of residential electricity demand. Renewable and Sustainable Energy Reviews, 37, 265-272. |
| [37] | Carvalho, L., & Rezai, A. (2015). Personal income inequality and aggregate demand. Cambridge Journal of Economics, 40 (2), 491-505. |
| [38] | Eid, R., & El-Gohary, H. (2015). The role of Islamic religiosity on the relationship between perceived value and tourist satisfaction. Tourism Management, 46, 477-488. |
| [39] | Huhtala, H. M. (2016). Finding educational insights in psychoanalytic theory with Marcuse and Adorno. Journal of Philosophy of Education, 50 (4): 689-704. |
| [40] | Carrington, M. J., Zwick, D., & Neville, B. (2016). The ideology of the ethical consumption gap. Marketing Theory, 16 (1), 21-38. |
| [41] | Tan, T. F., Netessine, S., & Hitt, L. (2017). Is tom cruise threatened? an empirical study of the impact of product variety on demand concentration. Information Systems Research, 28 (3): 643-660. |
| [42] | Trentin, A., Perin, E., & Forza, C. (2014). Increasing the consumer-perceived benefits of a mass-customization experience through sales-configurator capabilities. Computers in Industry, 65 (4), 693-705. |
| [43] | Yoo, J., & Park, M. (2016). The effects of e-mass customization on consumer perceived value, satisfaction, and loyalty toward luxury brands. Journal of Business Research, 69 (12): 5775-5784. |
| [44] | Jung, N. Y., & Seock, Y. K. (2017). Effect of service recovery on customers’ perceived justice, satisfaction, and word-of-mouth intentions on online shopping websites. Journal of Retailing and Consumer Services, (37): 23-30. |
| [45] | Vera, J., & Trujillo, A. (2013). Service quality dimensions and superior customer perceived value in retail banks: An empirical study on Mexican consumers. Journal of Retailing and Consumer Services, 20 (6), 579-586. |
| [46] | Flory, L., Osei-Bryson, K. M., & Thomas, M. (2017). A new web personalization decision-support artifact for utility-sensitive customer review analysis. Decision Support Systems, 94, 85-96. |
| [47] | Kim, Y., & Krishnan, R. (2015). On product-level uncertainty and online purchase behavior: An empirical analysis. Management Science, 61 (10): 2449-2467. |
| [48] | Wang, J. C., & Chang, C. H. (2013). How online social ties and product-related risks influence purchase intentions: A Facebook experiment. Electronic Commerce Research and Applications, 12 (5), 337-346. |
| [49] | Coenen, C., Alexander, K., & Kok, H. (2013). Facility management value dimensions from a demand perspective. Journal of Facilities Management, 11 (4), 339-353. |
| [50] | Coenen, C., & von Felten, D. (2014). A service-oriented perspective of facility management. Facilities, 32 (9/10), 554-564. |
| [51] | Coenen, C., Waldburger, D., & von Felten, D. (2013). FM servicebarometer: monitoring customer perception of service performance. Journal of Facilities Management, 11 (3), 266-278. |
| [52] | Anker Jensen, P., JM van der Voordt, T., Coenen, C., & Sarasoja, A. L. (2014). Reflecting on future research concerning the added value of FM. Facilities, 32 (13/14), 856-870. |
| [53] | Kannan, P. K. (2017). Digital marketing: A framework, review and research agenda. International Journal of Research in Marketing, 34 (1): 22-45. |
| [54] | Zhang, J., & Zhu, J. (2014). Research intelligent precision marketing of e-commerce based on the big data. Journal of Management and Strategy, 5 (1), 33. |
| [55] | You, Z., Si, Y. W., Zhang, D., Zeng, X., Leung, S. C., & Li, T. (2015). A decision-making framework for precision marketing. Expert Systems with Applications, 42 (7): 3357-3367. |
| [56] | Todd, S. Y., Crook, T. A., & Lachowetz, T. (2013). Agency theory expalnations of self-serving sales forecast inaccuracies. Business and Management Research, 2 (2).13-21. |
| [57] | Wang, M., Zuo, W., & Wang, Y. (2015). A multidimensional nonnegative matrix factorization model for retweeting behavior prediction. Mathematical Problems in Engineering, Article ID 936397, 10 pages. |
| [58] | Lam, J. S. L., & Dai, J. (2015). Developing supply chain security design of logistics service providers: An analytical network process-quality function deployment approach. International Journal of Physical Distribution & Logistics Management, 45 (7), 674-690. |
| [59] | Wu, Y. H., & Ho, C. C. (2015). Integration of green quality function deployment and fuzzy theory: a case study on green mobile phone design. Journal of Cleaner Production, 108, 271-280. |
| [60] | Nazari, M., & Foroud, A. A. (2013). Optimal strategy planning for a retailer considering medium and short-term decisions. International journal of Electrical power & Energy systems, 45 (1), 107-116. |
| [61] | Fancello, G., Paddeu, D., & Fadda, P. (2017). Investigating last food mile deliveries: A case study approach to identify needs of food delivery demand. Research in Transportation Economics, 65, 56-66. |
| [62] | Craig, N., DeHoratius, N., & Raman, A. (2016). The impact of supplier inventory service level on retailer demand. Manufacturing & Service Operations Management, 18 (4), 461-474. |
| [63] | Hainmueller, J., Hiscox, M. J., & Sequeira, S. (2015). Consumer demand for fair trade: Evidence from a multistore field experiment. Review of Economics and Statistics, 97 (2), 242-256. |
| [64] | Stratton, J. P., & Werner, M. J. (2013). Consumer behavior analysis of fair trade coffee: Evidence from field research. The Psychological Record, 63 (2), 363-374. |
| [65] | Hübner, A. H., Kuhn, H., & Sternbeck, M. G. (2013). Demand and supply chain planning in grocery retail: an operations planning framework. International Journal of Retail & Distribution Management, 41 (7), 512-530. |
| [66] | Hübner, A., Kuhn, H., & Wollenburg, J. (2016). Last mile fulfilment and distribution in omni-channel grocery retailing: a strategic planning framework. International Journal of Retail & Distribution Management, 44 (3), 228-247. |
| [67] | Wollenburg, J., Hübner, A., Kuhn, H., & Trautrims, A. (2018). From bricks-and-mortar to bricks-and-clicks: logistics networks in omni-channel grocery retailing. International Journal of Physical Distribution & Logistics Management, 48 (4), 415-438. |
| [68] | Holzapfel, A., Hübner, A., Kuhn, H., & Sternbeck, M. G. (2016). Delivery pattern and transportation planning in grocery retailing. European Journal of Operational Research, 252 (1), 54-68. |
| [69] | Zhong, H., Xie, L., & Xia, Q. (2013). Coupon incentive-based demand response: Theory and case study. IEEE Transactions on Power Systems, 28 (2), 1266-1276. |
| [70] | Alasseri, R., Rao, T. J., & Sreekanth, K. J. (2018). Conceptual framework for introducing incentive-based demand response programs for retail electricity markets. Energy Strategy Reviews, 19, 44-62. |
| [71] | Dupont, B., Dietrich, K., De Jonghe, C., Ramos, A., & Belmans, R. (2014). Impact of residential demand response on power system operation: A Belgian case study. Applied Energy, 122, 1-10. |
| [72] | Jouzdani, J., Sadjadi, S. J., & Fathian, M. (2013). Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case study of Tehran. Applied Mathematical Modelling, 37 (18-19), 8467-8483. |
| [73] | Cardoso, S. R., Barbosa-Póvoa, A. P. F., & Relvas, S. (2013). Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty. European Journal of Operational Research, 226 (3), 436-451. |
| [74] | Xu, D., Zhang, X., & Feng, H. (2018). Generalized fuzzy soft sets theory-based novel hybrid ensemble credit scoring model. International Journal of Finance & Economics. In Press. |
| [75] | Chu, H. L., Chen, Y. L., & Chiou, Y. Y. (2018). A field study of the impact of changes to a net sales-based incentive plan and centralized inventory management. Asia-Pacific Journal of Accounting & Economics, In Press. |
| [76] | Kjellsdotter Ivert, L., & Jonsson, P. (2014). When should advanced planning and scheduling systems be used in sales and operations planning? International Journal of Operations & Production Management, 34 (10), 1338-1362. |
| [77] | Zhao, Y., Yang, S., Narayan, V., & Zhao, Y. (2013). Modeling consumer learning from online product reviews. Marketing Science, 32 (1): 153-169. |
| [78] | Xie, K. L., Zhang, Z., & Zhang, Z. (2014a). The business value of online consumer reviews and management response to hotel performance. International Journal of Hospitality Management, 43, 1-12. |
| [79] | Xie, K. L., Chen, C., & Wu, S. (2016b). Online consumer review factors affecting offline hotel popularity: evidence from tripadvisor. Journal of Travel & Tourism Marketing, 33 (2), 211-223. |
| [80] | Floyd, K., Freling, R., Alhoqail, S., Cho, H. Y., & Freling, T. (2014). How online product reviews affect retail sales: A meta-analysis. Journal of Retailing, 90 (2), 217-232. |
| [81] | Wang, D., Li, Z., Dey, N., Ashour, A. S., Sherratt, R. S., & Shi, F. (2017). Case-based reasoning for product style construction and fuzzy analytic hierarchy process evaluation modeling using consumers linguistic variables. IEEE Access, 5, 4900-4912. |
| [82] | Gu, B., & Ye, Q. (2014). First step in social media: Measuring the influence of online management responses on customer satisfaction. Production and Operations Management, 23 (4), 570-582. |
| [83] | Filieri, R., & McLeay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews. Journal of Travel Research, 53 (1), 44-57. |
| [84] | Wee, C. S., Ariff, M. S. B. M., Zakuan, N., Tajudin, M. N. M., Ismail, K., & Ishak, N. (2014). Consumers perception, purchase intention and actual purchase behavior of organic food products. Review of Integrative Business and Economics Research, 3 (2), 378. |
| [85] | Ralston, R., & Abha, W. (2018). Factors Influencing the Purchase Intention and Actual Purchase behaviour of Organic Food in Urban India. Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics, 24 (3). 29-37. |
| [86] | Ueasangkomsate, P., & Santiteerakul, S. (2016). A study of consumers’ attitudes and intention to buy organic foods for sustainability. Procedia Environmental Sciences, 34, 423-430. |
| [87] | Bustinza, O., C. Parry, G., & Vendrell-Herrero, F. (2013). Supply and demand chain management: The effect of adding services to product offerings. Supply Chain Management: An International Journal, 18 (6), 618-629. |
| [88] | Roh, J., Hong, P., & Min, H. (2014). Implementation of a responsive supply chain strategy in global complexity: The case of manufacturing firms. International Journal of Production Economics, 147, 198-210. |
| [89] | Lei, N., & Moon, S. K. (2015). A Decision Support System for market-driven product positioning and design. Decision Support Systems, 69, 82-91. |
| [90] | Daas, D., Hurkmans, T., Overbeek, S., & Bouwman, H. (2013). Developing a decision support system for business model design. Electronic Markets, 23 (3), 251-265. |
| [91] | Liu, S. Y. (2018). Precision Marketing Scheme based on Integrating Spatio-temporal Data Clustering and Neural Network. In Journal of Physics Conference Series. 1087 (3): 032014. |
| [92] | Zhang, B., & Zhang, B (2018). Precise marketing of precision marketing value chain process on the H group line based on big data. Journal of Intelligent & Fuzzy Systems, 35 (3): 2837-2845. |
| [93] | Moradi, A., Razmi, J., Babazadeh, R., & Sabbaghnia, A. (2018). An integrated Principal Component Analysis and multi-objective mathematical programming approach to agile supply chain network design under uncertainty. Journal of Industrial & Management Optimization, 433-459. |
| [94] | Bai, X., & Liu, Y. (2016). Robust optimization of supply chain network design in fuzzy decision system. Journal of Intelligent Manufacturing, 27 (6), 1131-1149. |
| [95] | Xu, X., Zhang, W., Li, N., & Xu, H. (2015). A bi-level programming model of resource matching for collaborative logistics network in supply uncertainty environment. Journal of the Franklin Institute, 352 (9), 3873-3884. |
| [96] | Kwark, Y., Chen, J., & Raghunathan, S. (2014a). Online product reviews: Implications for retailers and competing manufacturers. Information systems research, 25 (1), 93-110. |
| [97] | Kwark, Y., Chen, J., & Raghunathan, S. (2017b). User-generated content and competing firms’ product design. Management Science, 64 (10), 4608-4628. |
| [98] | Du, J., Yang, Y., Li, D., & Zuo, J. (2017). Do investment and improvement demand outweigh basic consumption demand in housing market? Evidence from small cities in Jiangsu, China. Habitat International, (66): 24-31. |
| [99] | Bajari, P., Chan, P., Krueger, D., & Miller, D. (2013). A dynamic model of housing demand: Estimation and policy implications. International Economic Review, 54 (2), 409-442. |
| [100] | Cohen, M. C., Lobel, R., & Perakis, G. (2015). The impact of demand uncertainty on consumer subsidies for green technology adoption. Management Science, 62 (5), 1235-1258. |
| [101] | Amin, S. H., & Zhang, G. (2013a). A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 37 (6), 4165-4176. |
| [102] | Amin, S. H., & Zhang, G. (2013b). A three-stage model for closed-loop supply chain configuration under uncertainty. International Journal of Production Research, 51 (5), 1405-1425. |
| [103] | Amin, S. H., & Zhang, G. (2014c). Closed-loop supply chain network configuration by a multi-objective mathematical model. International Journal of Business Performance and Supply Chain Modelling, 6 (1), 1-15. |
| [104] | Tosarkani, B. M., & Amin, S. H. (2018). A possibilistic solution to configure a battery closed-loop supply chain: Multi-objective approach. Expert Systems with Applications, 92, 12-26. |
| [105] | Ardalan, Z., Karimi, S., Naderi, B., & Khamseh, A. A. (2016). Supply chain networks design with multi-mode demand satisfaction policy. Computers & Industrial Engineering, 96, 108-117. |
| [106] | Kazemi, Y., & Szmerekovsky, J. (2015). Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning. Transportation Research Part E: Logistics and Transportation Review, 83, 111-125. |
| [107] | Qu, Y., Bektaş, T., & Bennell, J. (2016). Sustainability SI: multimode multicommodity network design model for intermodal freight transportation with transfer and emission costs. Networks and Spatial Economics, 16 (1), 303-329. |
| [108] | Cohen, M. C., Lobel, R., & Perakis, G. (2018b). Dynamic pricing through data sampling. Production and Operations Management, 27 (6), 1074-1088. |
| [109] | Chen, X., Hu, P., & Hu, Z. (2016). Efficient algorithms for the dynamic pricing problem with reference price effect. Management Science, 63 (12), 4389-4408. |
| [110] | Baghalian, A., Rezapour, S., & Farahani, R. Z. (2013). Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case. European Journal of Operational Research, 227 (1), 199-215. |
| [111] | Pan, F., & Nagi, R. (2013). Multi-echelon supply chain network design in agile manufacturing. Omega, 41 (6), 969-983. |
| [112] | Sarkar, B., Saren, S., & Wee, H. M. (2013). An inventory model with variable demand, component cost and selling price for deteriorating items. Economic Modelling, 30, 306-310. |
| [113] | Jiang, Z., Zhou, T., Zhang, H., Wang, Y., Cao, H., & Tian, G. (2016). Reliability and cost optimization for remanufacturing process planning. Journal of cleaner production, 135, 1602-1610. |
| [114] | Wang, Y., Lu, X., & Tan, Y. (2018). Impact of product attributes on customer satisfaction: An analysis of online reviews for washing machines. Electronic Commerce Research and Applications, 29, 1-11. |
| [115] | Rad, M. A., Khoshalhan, F., & Glock, C. H. (2014). Optimizing inventory and sales decisions in a two-stage supply chain with imperfect production and backorders. Computers & Industrial Engineering, (74): 219-227. |
| [116] | Zhang, C., Gunasekaran, A., & Wang, W. Y. C. (2015). A comprehensive model for supply chain integration. Benchmarking: An International Journal, 22 (6), 1141-1157. |
| [117] | Gholamian, N., Mahdavi, I., Tavakkoli-Moghaddam, R., & Mahdavi-Amiri, N. (2015). Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty. Applied soft computing, 37, 585-607. |
| [118] | Darmawan, A., Wong, H., & Thorstenson, A. (2018). Integration of promotion and production decisions in sales and operations planning. International Journal of Production Research, 1-21. |
| [119] | Özer, Ö., & Uncu, O. (2015). Integrating dynamic time-to-market, pricing, production and sales channel decisions. European Journal of Operational Research, 242 (2), 487-500. |
| [120] | Giri, B. C., & Sharma, S. (2014). Manufacturer's pricing strategy in a two-level supply chain with competing retailers and advertising cost dependent demand. Economic Modelling, 38, 102-111. |
| [121] | Basiri, Z., & Heydari, J. (2017). A mathematical model for green supply chain coordination with substitutable products. Journal of cleaner production, 145, 232-249. |
| [122] | Jamali, M. B., & Rasti-Barzoki, M. (2018). A game theoretic approach for green and non-green product pricing in chain-to-chain competitive sustainable and regular dual-channel supply chains. Journal of Cleaner Production, 170, 1029-1043. |
| [123] | Boukherroub, T., Ruiz, A., Guinet, A., & Fondrevelle, J. (2015). An integrated approach for sustainable supply chain planning. Computers & Operations Research, 54, 180-194. |
| [124] | Khan, M., Hussain, M., & Saber, H. M. (2016). Information sharing in a sustainable supply chain. International Journal of Production Economics, 181, 208-214. |
| [125] | Sana, S. S. (2016). Optimal production lot size and reorder point of a two-stage supply chain while random demand is sensitive with sales teams' initiatives. International Journal of Systems Science, 47 (2), 450-465. |
| [126] | Cárdenas-Barrón, L. E., & Sana, S. S. (2014). A production-inventory model for a two-echelon supply chain when demand is dependent on sales teams׳ initiatives. International Journal of Production Economics, 155, 249-258. |
| [127] | Lin, T. Y. (2013). Coordination policy for a two-stage supply chain considering quantity discounts and overlapped delivery with imperfect quality. Computers & Industrial Engineering, 66 (1), 53-62. |
| [128] | Feng, Y., Martel, A., D'Amours, S., & Beauregard, R. (2013). Coordinated contract decisions in a make‐to‐order manufacturing supply chain: A stochastic programming approach. Production and Operations Management, 22 (3), 642-660. |
| [129] | Ivert, L. K., Dukovska-Popovska, I., Kaipia, R., Fredriksson, A., Dreyer, H. C., Johansson, M. I.,... & Tuomikangas, N. (2015). Sales and operations planning: responding to the needs of industrial food producers. Production Planning & Control, 26 (4), 280-295. |
| [130] | Lim, L. L., Alpan, G., & Penz, B. (2014). Reconciling sales and operations management with distant suppliers in the automotive industry: a simulation approach. International Journal of Production Economics, 151, 20-36. |
| [131] | Maslow, A. H. (1943). A theory of human motivation. Psychological Review. 50 (4): 370–96. |
| [132] | Morgenstern, O. (1948). Demand theory reconsidered. The Quarterly Journal of Economics, 62 (2): 165-201. |
| [133] | McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1953). Century psychology series. The achievement motive. East Norwalk, CT, US: Appleton-Century-Crofts. |
| [134] | Sethi, S. P., Yan, H., & Zhang, H. (2006). Inventory and supply chain management with forecast updates. Dordrecht: Springer Science & Business Media. |
| [135] | Kishtainy, N. (2017). A Little History of Economics. New Haven, CT: Yale University Press. |
| [136] | Gu, Z., & Tayi, G. K. (2015). Research Note—Investigating Firm Strategies on Offering Consumer-Customizable Products. Information Systems Research, 26 (2): 456-468. |
| [137] | Fisher, M. L., Hammond, J. H., Obermeyer, W. R., & Raman, A. (1994). Making supply meet demand in an uncertain world. Harvard business review, 72, 83-83. |
| [138] | Iyer, A. V., & Bergen, M. E. (1997). Quick response in manufacturer-retailer channels. Management Science, 43 (4), 559-570. |
| [139] | Barnes-Schuster, D., Bassok, Y., & Anupindi, R. (2002). Coordination and flexibility in supply contracts with options. Manufacturing & Service Operations Management, 4 (3), 171-207. |
| [140] | Hahl, O. (2016). Turning back the clock in baseball: The increased prominence of extrinsic rewards and demand for authenticity. Organization Science, 27 (4): 929-953. |
| [141] | Salvador, F., De Holan, P. M., & Piller, F. (2009). Cracking the code of mass customization. MIT Sloan management review, 50 (3): 71-78. |
| [142] | McIntosh, R. I., Matthews, J., Mullineux, G., & Medland, A. J. (2010). Late customisation: issues of mass customisation in the food industry. International Journal of Production Research, 48 (6), 1557-1574. |
| [143] | Chen, C., & Wang, L. (2008). Integrating rough set clustering and grey model to analyse dynamic customer requirements. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 222 (2), 319-332. |
| [144] | Vinodh, S., & Balaji, S. R. (2011). Fuzzy logic based leanness assessment and its decision support system. International Journal of Production Research, 49 (13), 4027-4041. |
| [145] | Boyd, H. W., Walker, O. C., & Larreche, J. C. (1998). Marketing management: A strategic approach with a global orientation. Burr Ridge, IL: Irwin Professional Publishing. |
| [146] | Armstrong, G., Adam, S., Denize, S., & Kotler, P. (2014). Principles of marketing. Pearson Australia. |
| [147] | Kanda, A., & Deshmukh, S. G. (2008). Supply chain coordination: perspectives, empirical studies and research directions. International journal of production Economics, 115 (2), 316-335. |
| [148] | Wold, S., Esbensen, K., & Geladi, P. (1987). Principal component analysis. Chemometrics and intelligent laboratory systems, 2 (1-3), 37-52. |
| [149] | Jolliffe, I. (2011). Principal component analysis. In International encyclopedia of statistical science (pp. 1094-1096). Springer, Berlin: Heidelberg. |
| [150] | Petroni, A., & Braglia, M. (2000). Vendor selection using principal component analysis. Journal of supply chain management, 36 (1), 63-69. |
APA Style
Zhiyi Zhuo. (2019). Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction. Mathematics and Computer Science, 4(2), 41-56. https://doi.org/10.11648/j.mcs.20190402.11
ACS Style
Zhiyi Zhuo. Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction. Math. Comput. Sci. 2019, 4(2), 41-56. doi: 10.11648/j.mcs.20190402.11
AMA Style
Zhiyi Zhuo. Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction. Math Comput Sci. 2019;4(2):41-56. doi: 10.11648/j.mcs.20190402.11
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Download@article{10.11648/j.mcs.20190402.11,
author = {Zhiyi Zhuo},
title = {Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction},
journal = {Mathematics and Computer Science},
volume = {4},
number = {2},
pages = {41-56},
doi = {10.11648/j.mcs.20190402.11},
url = {https://doi.org/10.11648/j.mcs.20190402.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20190402.11},
abstract = {Demand management research has always attracted considerable attention from academia and industry, covering almost all fields, including multiple disciplines, including philosophy, economics, mathematics, management, psychology, etc. This paper provides a systematic review of 110 peer-reviewed journal articles published from 2013 to 2018. The primary purpose is to study how companies design and plan optimal product sales decisions under different demand patterns. We passed to organize and analyze these 110 articles, summarizing the specific role of demand on the consumer goods supply chain, and the relationship to corporate sales decisions. We found that customer demand has driving force and starting point for suppliers to make product sales decisions in the field of consumer goods supply chain. The customer demand for products dramatically affects the degree of market segmentation and also determines the benefits of manufacturers and retailers. However, the existing research is only done under the uncertainty of demand and does not consider the three different demand patterns, real, false, and semi-real. Therefore, there is a significant theoretical gap in existing research. Our goal is to establish a theoretical bridge through the combing and review of relevant literature systems and to construct a conceptual model of the demand-oriented supply chain. This conceptual model will provide an essential reference for the direction of future research.},
year = {2019}
}
TY - JOUR T1 - Supply Chain from the Demand Orientation: A Systematic Literature Review and Theoretical Model Construction AU - Zhiyi Zhuo Y1 - 2019/09/16 PY - 2019 N1 - https://doi.org/10.11648/j.mcs.20190402.11 DO - 10.11648/j.mcs.20190402.11 T2 - Mathematics and Computer Science JF - Mathematics and Computer Science JO - Mathematics and Computer Science SP - 41 EP - 56 PB - Science Publishing Group SN - 2575-6028 UR - https://doi.org/10.11648/j.mcs.20190402.11 AB - Demand management research has always attracted considerable attention from academia and industry, covering almost all fields, including multiple disciplines, including philosophy, economics, mathematics, management, psychology, etc. This paper provides a systematic review of 110 peer-reviewed journal articles published from 2013 to 2018. The primary purpose is to study how companies design and plan optimal product sales decisions under different demand patterns. We passed to organize and analyze these 110 articles, summarizing the specific role of demand on the consumer goods supply chain, and the relationship to corporate sales decisions. We found that customer demand has driving force and starting point for suppliers to make product sales decisions in the field of consumer goods supply chain. The customer demand for products dramatically affects the degree of market segmentation and also determines the benefits of manufacturers and retailers. However, the existing research is only done under the uncertainty of demand and does not consider the three different demand patterns, real, false, and semi-real. Therefore, there is a significant theoretical gap in existing research. Our goal is to establish a theoretical bridge through the combing and review of relevant literature systems and to construct a conceptual model of the demand-oriented supply chain. This conceptual model will provide an essential reference for the direction of future research. VL - 4 IS - 2 ER -
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