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<p class="HTMLBody"><span lang="EN-US" style="font-size:11.0pt;font-family:"Candara","sans-serif"">********************* CALL FOR PAPERS *********************<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">SUBMISSION DUE DATE: February 15, 2015<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";text-transform:uppercase;mso-fareast-language:FR">Reviewer first reports</span><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">:
June 15, 2015<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";text-transform:uppercase;mso-fareast-language:FR">Revised paper submission</span><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">:
September 15, 2015<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";text-transform:uppercase;mso-fareast-language:FR">Reviewer second reports</span><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">:
December 10, 2015<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";text-transform:uppercase;mso-fareast-language:FR">Final manuscript submissions to publisher</span><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">:
March 15, 2016<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">SPECIAL ISSUE ON
<b>Big Data and Business Analytics Adoption and Use: A Step toward Transforming Operations and Production Management?<o:p></o:p></b></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">International Journal of Operations & Production Management
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Guest Editors:
<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Dr Samuel Fosso Wamba, Associate Professor, NEOMA Business School, France<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">Dr Andrew Taylor, Professor, Bradford University School of Management, UK<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">Dr Eric Ngai, Professor, The Hong Kong Polytechnic University, Hong Kong<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">Dr Fred Riggins, Associate Professor, North Dakota State University, USA<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-family:"Candara","sans-serif"">Introduction:</span></b><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-AU" style="font-family:"Candara","sans-serif"">Big data analytics is defined as “<i>a collection of data and technology that accesses, integrates, and reports all available data by filtering, correlating,
and reporting insights not attainable with past data technologies</i>” (</span><a href="#_ENREF_1" title="APICS, 2012 #21792"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">APICS 2012</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">).
It is an emerging phenomenon which reflects the ever increasing significance of data in terms of its growing volumes, variety and velocity (the speed with which it is being created and processed) (</span><a href="#_ENREF_3" title="Department for Business- Innovation and Skills, 2013 #21793"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Department
for Business- Innovation and Skills 2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">). While data has always been a part of the Information and Communication Technology (ICT) agenda, it is the scale and scope of change which big
data is bringing that has attracted so much attention. Like many new phenomena it is sometimes over-sold because of hype or misunderstanding, yet there are tangible case studies of the power of big data to generate value and competitive advantage, albeit such
examples remain comparatively small in number to-date. Its applications have been strong in the financial services, insurance, retailing and healthcare sectors, while in manufacturing, companies such as Rolls Royce and Ford have been reported to derive success
from big data in predicting engine failures before they occur and in managing supplier risk (</span><a href="#_ENREF_6" title="Goodwin, 2013 #21794"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Goodwin
2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">).<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-AU" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-AU" style="font-family:"Candara","sans-serif"">For Operations Management, big data has the potential to enable more sophisticated data-driven decision making and new ways to organise, learn and
innovate (</span><a href="#_ENREF_13" title="Yiu, 2012 #21796"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Yiu 2012</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">;
</span><a href="#_ENREF_7" title="Kiron, 2013 #21795"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Kiron 2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">). Its impact may be
manifest in strengthening customer relationships, managing operations risk, improving operational efficiency or by improving product or service delivery or whatever the key business drivers may be (</span><a href="#_ENREF_7" title="Kiron, 2013 #21795"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Kiron
2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">). Operations in many organisations are experiencing much more voluminous and unstructured data environments because of real-time information from sensors and RFID tags which facilitate
asset and business process monitoring (</span><a href="#_ENREF_2" title="Davenport, 2012 #21797"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Davenport, Barth et al. 2012</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">),
end-to-end supply chain visibility, improved manufacturing and industrial automation (</span><a href="#_ENREF_12" title="Wilkins, 2013 #21784"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Wilkins 2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">),
manufacturing efficiency and effectiveness (</span><a href="#_ENREF_14" title="Zelbst, 2011 #19139"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Zelbst, Green et al. 2011</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">).
Ford, for example, is reported to be scouring “<i>the metrics from the company's best processes across myriad manufacturing efforts and through detailed outputs from in-use automobiles--all to improve and help transform its business.</i>” (</span><a href="#_ENREF_4" title="Gardner, 2013 #21798"><span lang="EN-AU" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Gardner
2013</span></a><span lang="EN-AU" style="font-family:"Candara","sans-serif"">). However, despite some reported successes, OM researchers need to retain a healthy scepticism until rigorous research has been done in operations contexts. That is why this new
phenomenon should have the attention of OM researchers, and hence this call for papers.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">Given its high operational and strategic potential, notably in generating business value within various industries, big data has recently become the
focus of a variety of scholars and practitioners. Some researchers have recently suggested that “big data” is the “next big thing in innovation” (</span><a href="#_ENREF_5" title="Gobble, 2013 #309"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Gobble
2013, p.64</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">), “the fourth paradigm of science” (Strawn, (</span><a href="#_ENREF_10" title="Strawn, 2012 #21040"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">2012</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">)),
or “the next frontier for innovation, competition, and productivity” (</span><a href="#_ENREF_9" title="Manyika, 2011 #193"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Manyika, Chui et al. 2011, p.1</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">).
As a result, challenges related to big data have confronted businesses and organizations. In the operations and service contexts, big data also holds tremendous potential. In a recent survey study on third-party logistics services (3PL), (</span><a href="#_ENREF_8" title="Langley, 2014 #21351"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Langley
2014</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">) found that 97% of shippers and 93% of 3PLs “feel strongly that improved, data-driven decision-making is essential to the future success of their supply chain activities and processes”
(p. 4), whereas approximately</span><span lang="EN-US"> </span><span lang="EN-US" style="font-family:"Candara","sans-serif"">50% of each group disagrees that “big data fuels these decisions” which shows how much potential for big data has still to be realized
(p. 4). Big retailers are currently leveraging big data capabilities for improved customer experience, fraud reduction, and just-in-time recommendations (</span><a href="#_ENREF_11" title="Tweney, 2013 #1"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Tweney
2013</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">).<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">In addition, big data technologies can be implemented in a range of applications including industrial </span><a href="http://www.dpaonthenet.net/products/183/Control-Automation"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">automation</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">
tools, building management systems, production equipment, sales force information systems, and power plan conditions tools. For example, big data enabled-automation and manufacturing facilitates real-time detection and diagnosis of production issues, and thus
reduces significantly downtime costs. Similarly, insights from big data analytics allows real-time process monitoring and measurement for improved quality management, logistics and order fulfilment cycles (</span><a href="#_ENREF_12" title="Wilkins, 2013 #21784"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Wilkins
2013</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">). In short, “<i>by observing causal factors for quality issues, process variability and energy efficiency through the manufacturing process, big data analysis becomes the basis for
gaining a competitive advantage</i>”(</span><a href="#_ENREF_12" title="Wilkins, 2013 #21784"><span lang="EN-US" style="font-family:"Candara","sans-serif";color:windowtext;text-decoration:none">Wilkins 2013</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif"">).<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-AU" style="font-family:"Candara","sans-serif";background:white"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">Even if big data holds the capability of transforming competition and thus competitive advantage, many managers are still struggling to understand
the concepts related to big data, consequently failing to capture business value from big data. In addition, very few empirical studies have been conducted on the real value from big data.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Objective:<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">The main objective of this special issue is to fill this knowledge gap. Specifically, this special issue aims to invite OM scholars and practitioners
to look at the ways and means to co-create and capture business value from big data in terms of new business opportunities, improved performance, and competitive advantage. The results will in turn reveal the implications of big data on operations management
practices and strategies.<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";color:#333333;background:white;mso-fareast-language:FR"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Recommended Topics:</span></b><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">The topics to be discussed in this special issue include but are not limited to the following:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR"><o:p> </o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:53.4pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Assessment of the effect of big data on operations and production management systems<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:54.0pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Assessment of the effect of big data on the decision-making processes in operations<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:54.0pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Assessment of facilitators and inhibitors of big data adoption for logistics, order fulfilment, distribution and supply chain management
<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:53.4pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Big data-enabled business analytics at the plant location , organizational, and supply chain levels<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:53.4pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">In-depth & longitudinal case studies and pilot studies on the implementation of IT infrastructure to support big data initiatives for improved operations management,
lean & agile operations, quality management in operations and supply chain management
<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:54.0pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Facilitation of innovative electronic business models and operations by using big data in various sectors (e.g., healthcare, retail industry, and manufacturing)<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:53.4pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">New theory development to explain the adoption and use of big data in operations at the organizational and inter-organizational levels<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:54.0pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Empirical studies assessing the business value of big data in terms of quality management, new products and services design, improved internal and supply chain operations
capabilities<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:54.0pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Social media and big data in cloud for services, operations and production management transformation
<o:p></o:p></span></p>
<p class="MsoNormalCxSpMiddle" style="margin-left:53.4pt;mso-add-space:auto;text-align:justify;text-indent:-18.0pt;mso-list:l0 level1 lfo2;text-autospace:none">
<![if !supportLists]><span lang="EN-US" style="font-family:Symbol"><span style="mso-list:Ignore">·<span style="font:7.0pt "Times New Roman"">
</span></span></span><![endif]><span lang="EN-US" style="font-family:"Candara","sans-serif"">Placement of data analytics and big data in cloud for services, operations and production management transformation
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Submission Procedure<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify;background:white"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white">Prospective authors</span><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">
are invited to submit papers for this special thematic issue on <b>“</b></span><b><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">Big Data Adoption and Use: A Step toward Transforming Operations and Production Management<span style="background:white">”</span></span></b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">
on or before February 15, 2015. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at
</span><a href="http://www.emeraldinsight.com/products/journals/author_guidelines.htm?id=ijopm"><span lang="EN-US">http://www.emeraldinsight.com/products/journals/author_guidelines.htm?id=ijopm</span></a><span class="apple-converted-space"><span style="font-family:"Candara","sans-serif";background:white">
</span></span><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white">PRIOR TO SUBMISSION at:
</span><a href="http://mc.manuscriptcentral.com/ijopm"><span lang="EN-US">http://mc.manuscriptcentral.com/ijopm</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white">.
</span><b><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><o:p></o:p></span></b></p>
<p class="MsoNormalCxSpMiddle" style="margin-bottom:6.0pt;mso-add-space:auto;text-align:justify">
<b><span lang="EN-US" style="font-family:"Candara","sans-serif";color:#333333;background:white"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";color:#333333;background:white">About
</span></b><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR">International Journal of Operations & Production Management Journal</span><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">The International Journal of Operations & Production Management exists to provide a communication medium for all those working in the operations management
field. This includes:<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">• Private and public sectors
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">• Manufacturing and service settings<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">• Academic institutions
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">• Consultancies.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif"">The content of the Journal focuses on topics which have a substantial management (as opposed to technical) content. A double-blind review process ensures
the journal content's high quality, validity and relevance.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";color:#333333;background:white">Editor-in-Chief:</span></b><span lang="EN-US" style="font-family:"Candara","sans-serif""> Professor Steve Brown<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif"">University of Exeter Business School, UK<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR"><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">All inquiries should be directed to the attention of:<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";mso-fareast-language:FR"><br>
<span style="background:white">Samuel Fosso Wamba<o:p></o:p></span></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">Guest Editor<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">E-mail:<span style="color:#333333"> </span></span><a href="mailto:samuel.fosso.wamba@neoma-bs.fr"><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">samuel.fosso.wamba@neoma-bs.fr</span></a><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif"">All manuscript submissions to the special issue should be sent through the online submission system:
<o:p></o:p></span></b></p>
<p class="MsoNormal"><a href="http://mc.manuscriptcentral.com/ijopm"><span lang="EN-US">http://mc.manuscriptcentral.com/ijopm</span></a><span style="font-family:"Candara","sans-serif"">
</span><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p></o:p></span></p>
<p class="MsoNormal" align="center" style="text-align:center;text-autospace:none">
<b><span lang="EN-US" style="font-size:16.0pt;font-family:"Candara","sans-serif"">* * * * * *<o:p></o:p></span></b></p>
<p style="margin:0cm;margin-bottom:.0001pt;text-align:justify"><b><span lang="EN-AU" style="font-family:TimesNewRoman;mso-fareast-language:EN-US">Samuel Fosso Wamba, PhD.,
</span></b><span lang="EN-AU" style="font-family:TimesNewRoman;mso-fareast-language:EN-US">is Associate Professor at NEOMA Business School, France. Prior, he was a Senior lecturer at the School of Information Systems & Technology (SISAT), University of Wollongong,
Australia. He earned an MSc in mathematics, from the University of Sherbrooke in Canada, an MSc in e-commerce from HEC Montreal, Canada, and a Ph.D. in industrial engineering, from the Polytechnic School of Montreal, Canada. His current research focuses on
business value of IT, business analytics, big data, inter-organisational system (e.g., RFID technology) adoption and use, e-government (e.g., open data), supply chain management, electronic commerce and mobile commerce. He has published papers in a number
of international conferences and journals including <i>European Journal of Information Systems</i>,
<i>Production Planning and Control</i>, <i>International Journal of Production Economics</i>,
<i>Information Systems Frontiers</i>, <i>Business Process Management Journal</i>,
<i>Proceedings of the IEEE, AMCIS, HICSS, ICIS, and PACIS</i>. He is organizing special issues on IT related topics for the Business Process Management Journal, Pacific Asia Journal of the Association for Information Systems, Journal of Medical Systems, Journal
of Theoretical and Applied Electronic Commerce Research, Journal of Organizational and End User Computing, and Production Planning & Control.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif""><o:p> </o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif"">Andrew Taylor, PhD<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif";color:black;mso-fareast-language:EN-GB">Andrew Taylor is Professor of Operations and Information Systems at Bradford School of Management,
Andrew teaches World Class Operations, Resource Planning for Operations and Environmental Management & Quality Systems. He specialises in research relating to organisational performance improvement approaches such as Lean Systems, Performance Measurement and
applications of new technologies such as Data Mining, Knowledge Management and 3D Printing. Professor Taylor has professional experience in aerospace, public utilities and government organisations, having worked in Short Brothers (now part of the Bombardier
group), Northern Ireland Electricity and the Northern Ireland Training Authority. He has consulted widely. As a graduate of The Queen’s University of Belfast, Andrew holds a BSc in electronics and information systems, an MSc in industrial engineering and a
PhD in manufacturing management. Previously Andrew Taylor was Professor of Information Management at Queen’s, Belfast where he worked for 12 years before coming to Bradford in 1996. His research work has been published in
<i>Omega, International Journal of Operations and Production Management, International Journal of Production Economics, Expert Systems with Applications, European Journal of Information Systems, Communications of the ACM,</i>
<i>Information Systems Management</i>, <i>Production Planning and Control </i>and the
<i>International Journal of Production Research</i>.<o:p></o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif""><o:p> </o:p></span></b></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif"">Eric W. T. Ngai, PhD<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif";letter-spacing:-.15pt">Prof. Eric Ngai is a Professor in the Department of Management and Marketing at The Hong Kong Polytechnic
University. His current research interests are in the areas of E-commerce, Supply Chain Management, Decision Support Systems and RFID Technology and Applications. He has over 100 refereed international journal publications including
<i>MIS Quarterly, Journal of Operations Management, Decision Support Systems, IEEE Transactions on Systems, Man and Cybernetics, Production & Operations Management,</i> and others.</span><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif"">
He is an Associate Editor of <i>European Journal of Information Systems</i> and <i>
Information & Management</i>. He serves on editorial board of four international journals.<span style="letter-spacing:-.15pt">
</span></span><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif"">Prof. Ngai has attained an
<i>h</i>-index of 20, and received 1190 citations, <i>ISI Web of Science</i>.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif"">Fred Riggins, PhD<o:p></o:p></span></b></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-GB" style="font-size:12.0pt;font-family:"Times New Roman","serif";letter-spacing:-.15pt">Fred Riggins is Associate Professor in the College of Business at North Dakota State University. His research
focuses on e-commerce</span><span lang="EN-US" style="font-size:12.0pt;font-family:"Times New Roman","serif"">, inter-organizational systems, RFID, and microfinance. He has published in leading journals including
<i>Management Science</i>, <i>Journal of Management Information Systems</i>, <i>Journal of the Association for Information Systems, International Journal of RF Technologies</i>,
<i>Electronic Commerce Research and Applications</i>, and <i>Communications of the ACM</i>. In a 2009 AIS publication, he ranked #9 on the list of top IS researchers from 2003-2007 based on number of publications and outlets. According to Google Scholar he
has an <i>h</i>-index of 19 and over 2,500 citations. <o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Candara","sans-serif";background:white;mso-fareast-language:FR">References:</span></b><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_1"><span lang="EN-US">APICS (2012). APICS 2012 Big Data Insights and Innovations Executive Summary.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_2"><span lang="EN-US">Davenport, T. H., P. Barth, et al. (2012). "How Big Data Is Different."
<u>MIT Sloan Management Review</u> <b>54</b>(1): 43-46.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_3"><span lang="EN-US">Department for Business- Innovation and Skills (2013). Seizing the data opportunity: A strategy for UK data capability
</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_4"><span lang="EN-US">Gardner, D. (2013). "Ford scours for more big data to bolster quality, improve manufacturing, streamline processes." Retrieved 19th February 2014, from
</span></a><a href="http://www.zdnet.com/ford-scours-for-more-big-data-to-bolster-quality-improve-manufacturing-streamline-processes-7000010451/"><span lang="EN-US">http://www.zdnet.com/ford-scours-for-more-big-data-to-bolster-quality-improve-manufacturing-streamline-processes-7000010451/</span></a><span lang="EN-US">.<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_5"><span lang="EN-US">Gobble, M. M. (2013). "Big Data: The Next Big Thing in Innovation."
<u>Research Technology Management</u> <b>56</b>(1): 64-66.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_6"><span lang="EN-US">Goodwin, G. (2013). Takeaways from the MIT/Accenture Big Data in Manufacturing Conference.
<u>MIT/Accenture Big Data in Manufacturing conference </u>Cambridge, USA.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_7"><span lang="EN-US">Kiron, D. (2013). "Organizational Alignment is Key to Big Data Success."
<u>MIT Sloan Management Review</u> <b>54</b>(3): 1-n/a.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_8"><span lang="EN-US">Langley, J. C. J. (2014). 2014 THIRD-PARTY LOGISTICS STUDY: The State of Logistics Outsourcing. Capgemini Consulting<b>:
</b>56pp.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_9"><span lang="EN-US">Manyika, J., M. Chui, et al. (2011). Big data: The next frontier for innovation, competition, and productivity, McKinsey Global Institute.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_10"><span lang="EN-US">Strawn, G. O. (2012). "Scientific Research: How Many Paradigms?"
<u>EDUCAUSE Review</u> <b>47</b>(3): 26.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_11"><span lang="EN-US">Tweney, D. (2013). "Walmart scoops up Inkiru to bolster its ‘big data’ capabilities online." Retrieved 15 October, 2013, from
</span></a><a href="http://venturebeat.com/2013/06/10/walmart-scoops-up-inkiru-to-bolster-its-big-data-capabilities-online/"><span lang="EN-US">http://venturebeat.com/2013/06/10/walmart-scoops-up-inkiru-to-bolster-its-big-data-capabilities-online/</span></a><span lang="EN-US">.<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_12"><span lang="EN-US">Wilkins, J. (2013). "Big data and its impact on manufacturing." Retrieved 17 February, 2014, from
</span></a><a href="http://www.dpaonthenet.net/article/65238/Big-data-and-its-impact-on-manufacturing.aspx"><span lang="EN-US">http://www.dpaonthenet.net/article/65238/Big-data-and-its-impact-on-manufacturing.aspx</span></a><span lang="EN-US">.<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_13"><span lang="EN-US">Yiu, C. (2012). The Big Data Opportunity: Making Government faster, smarter and more personal.
<u>Policy Exchange</u>. London<b>: </b>36.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-left:36.0pt;text-align:justify;text-indent:-36.0pt">
<a name="_ENREF_14"><span lang="EN-US">Zelbst, P. J., K. W. J. R. Green, et al. (2011). "Radio Frequency Identification Techonology Utilization and Organizational Agility."
<u>The Journal of Computer Information Systems</u> <b>52</b>(1): 24-33.</span></a><span lang="EN-US"><o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="EN-US" style="font-family:"Candara","sans-serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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